# kb

id: eastin-knill-theorem-20260505-0
file: data/en.wikipedia.org/wiki/Eastin–Knill_theorem-0.md
category: reference
title: Eastin–Knill theorem
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eastin–Knill_theorem
date_saved: 2026-05-05T11:06:55.634034+00:00
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parent: eastin-knill-theorem-20260505-0
summary:
The Eastin–Knill theorem is a no-go theorem that states: "No quantum error correcting code can have a continuous symmetry which acts transversely on physical qubits". In other words, no quantum error correcting code can transversely implement a universal gate set that contains only unitary gates, where a transversal logical gate is one that can be implemented on a logical qubit by the independent action of separate physical gates on corresponding physical qubits. In addition to investigating fault tolerant quantum computation, the Eastin–Knill theorem is also useful for studying quantum gravity via the AdS/CFT correspondence and in condensed matter physics via quantum reference frame or many-body theory. The theorem is named after Bryan Eastin and Emanuel Knill, who published it in 2009. == Description == Since quantum computers are inherently noisy, quantum error correcting codes are used to correct errors that affect information due to decoherence and dissipation. Decoding error corrected data in order to perform gates on the qubits makes it prone to errors. Fault tolerant quantum computation avoids this by performing gates on encoded data. Transversal gates, which perform a gate between two logical qubits each of which is encoded in N physical qubits by pairing up the physical


id: electron-on-helium-qubit-20260505-0
file: data/en.wikipedia.org/wiki/Electron-on-helium_qubit-0.md
category: reference
title: Electron-on-helium qubit
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Electron-on-helium_qubit
date_saved: 2026-05-05T11:06:56.851379+00:00
instance: kb-cron
parent: electron-on-helium-qubit-20260505-0
summary:
An electron-on-helium qubit is a quantum bit for which the orthonormal basis states |0⟩ and |1⟩ are defined by quantized motional states or alternatively the spin states of an electron trapped above the surface of liquid helium. The electron-on-helium qubit was proposed as the basic element for building quantum computers with electrons on helium by Platzman and Dykman in 1999. == History of electrons on helium == The electrostrictive binding of electrons to the surface of liquid helium was first demonstrated experimentally by Bruschi and co-workers in 1966. A theoretical treatment of the electron-helium interaction was developed by Cole and Cohen in 1969 and, independently, by Shikin in 1970. An electron close to the surface of liquid helium experiences an attractive force due to the formation of a weak (~0.01e) image charge in the dielectric liquid. However, the electron is prevented from entering the liquid by a high (~1 eV) barrier formed at the surface due to the hard-core repulsion of the electron by the helium atoms. As a result, the electron remains trapped outside the liquid. The energy of the electron in this potential well is quantised in a Hydrogen-like series with the modified Rydberg constant RHe ≈ {\displaystyle


id: electron-on-helium-qubit-20260505-1
file: data/en.wikipedia.org/wiki/Electron-on-helium_qubit-1.md
category: reference
title: Electron-on-helium qubit
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Electron-on-helium_qubit
date_saved: 2026-05-05T11:06:56.851379+00:00
instance: kb-cron
parent: electron-on-helium-qubit-20260505-0
summary:
== Decoherence == In any quantum computer the decoherence of the qubit wavefunction, due to energy relaxation or dephasing effects, must be limited to a suitably low rate. For electron-on-helium qubits, deformations of the helium surface due to surface or bulk excitations (ripplons or phonons) modify the image charge potential and distort the electron wavefunction. Therefore, for Rydberg and orbital states, the primary source of decoherence is expected to be the emission of ripplons or phonons in the helium substrate. However, the decay rate due to these processes is expected to be slow (~100 μs) compared with the rate at which qubit operations can be performed (~10 ns). For the spin state, the inherent purity of the qubit environment and the weak spin orbit interaction for an electron moving above the helium surface results in predicted coherence times > {\displaystyle >} 1 s. == Current developments == The first trapping and detection of single electrons on helium was demonstrated by Lea and co-workers in 2005, using a micrometer-scale helium-filled trap and a single electron transistor beneath the surface to count the electrons. This experiment also demonstrated the first coupling between an electron on helium and a superconducting quantum circuit. Subsequently,


id: marcos-eduardo-elias-20260505-0
file: data/en.wikipedia.org/wiki/Marcos_Eduardo_Elias-0.md
category: reference
title: Marcos Eduardo Elias
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Marcos_Eduardo_Elias
date_saved: 2026-05-05T11:06:57.999873+00:00
instance: kb-cron
parent: marcos-eduardo-elias-20260505-0
summary:
Marcos Eduardo Elias (São Paulo, May 16, 1971) is a Brazilian entrepreneur with a background in mathematics, engineering, and financial markets. He has worked in investment and financial analysis and has been associated with initiatives related to quantum computing in Brazil. == Career == Elias built his career in the financial sector, working as an investment analyst and later as a fund manager and entrepreneur. He held positions at institutions including Banco Bozano Simonsen and BNP Paribas, where he became chief analyst in Brazil. He was later involved in founding and development of investment and research firms such as Empiricus and other financial ventures. He has also worked in academia, teaching at institutions including Insper and Fundação Getulio Vargas. == Legal Issues == In 2018, Elias was arrested in Switzerland at the request of United States authorities in connection with an investigation into financial fraud. According to the United States Department of Justice, he was accused of participating in a scheme involving international bank transfers, the use of false identities, and offshore companies. He was later extradited to the United States, where he faced charges related to wire fraud and aggravated identity theft. In 2019, he pleasded guilty and was


id: entanglement-swapping-20260505-0
file: data/en.wikipedia.org/wiki/Entanglement_swapping-0.md
category: reference
title: Entanglement swapping
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Entanglement_swapping
date_saved: 2026-05-05T11:06:59.127187+00:00
instance: kb-cron
parent: entanglement-swapping-20260505-0
summary:
In quantum mechanics, entanglement swapping is a protocol to transfer quantum entanglement from one pair of particles to another, even if the second pair of particles have never interacted. This process may have application in quantum communication networks and quantum computing. == Concept == === Basic principles === Entanglement swapping has two pairs of entangled particles: (A, B) and (C, D). Pair of particles (A, B) is initially entangled, as is the pair (C, D). The pair (B, C) taken from the original pairs, is projected onto one of the four possible Bell states, a process called a Bell state measurement. The unmeasured pair of particles (A, D) can become entangled. This effect happens without any previous direct interaction between particles A and D. Entanglement swapping is a form of quantum teleportation. In quantum teleportation, the unknown state of a particle can be sent from one location to another using the combination of a quantum and classical channel. The unknown state is projected by Alice onto a Bell state and the result is communicated to Bob through the classical channel. In entanglement swapping, the state from one of the two sources is the quantum channel of teleportation and the state


id: fault-tolerant-quantum-computing-20260505-0
file: data/en.wikipedia.org/wiki/Fault_tolerant_quantum_computing-0.md
category: reference
title: Fault tolerant quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fault_tolerant_quantum_computing
date_saved: 2026-05-05T11:07:00.326482+00:00
instance: kb-cron
parent: fault-tolerant-quantum-computing-20260505-0
summary:
In quantum information, fault-tolerant quantum computing (FTQC) is a regime of quantum processors that are both large-scale and that effectively incorporate quantum error correction to achieve arbitrarily low error rates (i.e. their logical error rate is much lower than their physical error rate). Full-FTQC processors are theoretically possible, but have not yet been realized experimentally. They are often seen as the primary end goal of quantum processor development, and are used to contrast with existing noisy intermediate-scale quantum (NISQ) quantum processors, which are subject to noise and decoherence preventing scalable error correction. One way FTQC devices can be realized is by grouping together multiple physical qubits to create a single logical qubit, and using error correction methods such as the surface code so that the combined system is fault-tolerant. Proposed FTQC devices generally include hundreds of logical (error-corrected) qubits, which would mean thousands of physical qubits at minimum. The transition from NISQ-era devices to the FTQC regime is an open research topic in quantum information. It is likely that advances at both the hardware and algorithm level are necessary for the transition to occur. == History == When quantum computers were initially theorized, it was unclear whether they would be


id: richard-feynman-20260505-0
file: data/en.wikipedia.org/wiki/Richard_Feynman-0.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
instance: kb-cron
parent: richard-feynman-20260505-0
summary:
Richard Phillips Feynman (; May 11, 1918 – February 15, 1988) was an American theoretical physicist. He shared the 1965 Nobel Prize in Physics with Julian Schwinger and Shin'ichirō Tomonaga "for their fundamental work in quantum electrodynamics (QED), with deep-ploughing consequences for the physics of elementary particles". He is also known for his work in the path integral formulation of quantum mechanics, the theory of the physics of the superfluidity of supercooled liquid helium, and the parton model. Feynman developed a pictorial representation scheme for the mathematical expressions describing the behavior of subatomic particles, which later became known as Feynman diagrams and remains widely used. He assisted in the development of the atomic bomb during World War II and became known to the wider public in the 1980s as a member of the Rogers Commission, the panel that investigated the Space Shuttle Challenger disaster. Along with his work in theoretical physics, Feynman has been credited with having pioneered the field of quantum computing and introducing the concept of nanotechnology. He held the Richard C. Tolman professorship in theoretical physics at the California Institute of Technology. In a 1999 poll of 130 leading physicists worldwide by the British journal Physics World,


id: richard-feynman-20260505-1
file: data/en.wikipedia.org/wiki/Richard_Feynman-1.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
summary:
== Education == Feynman attended Far Rockaway High School, which was also attended by fellow Nobel laureates Burton Richter and Baruch Samuel Blumberg. Upon starting high school, Feynman was quickly promoted to a higher math class. An IQ test administered in high school estimated his IQ at 125—high but "merely respectable", according to biographer James Gleick. His sister Joan, who scored one point higher, later jokingly claimed to an interviewer that she was smarter. Years later he declined to join Mensa International, saying that his IQ was too low. When Feynman was 15, he taught himself trigonometry, advanced algebra, infinite series, analytic geometry, and both differential and integral calculus. Before entering college, he was experimenting with mathematical topics such as the half-derivative using his own notation. He created special symbols for logarithm, sine, cosine and tangent functions so they did not look like three variables multiplied together, and for the derivative, to remove the temptation of canceling out the d {\displaystyle d} s in d / d x {\displaystyle d/dx} . A member of the Arista Honor Society, in his last year in high school he won the New York University Math Championship. His habit of direct characterization sometimes rattled


id: richard-feynman-20260505-2
file: data/en.wikipedia.org/wiki/Richard_Feynman-2.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
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In 1941, with World War II occurring in Europe but the United States not yet at war, Feynman spent the summer working on ballistics problems at the Frankford Arsenal in Pennsylvania. After the attack on Pearl Harbor brought the United States into the war, Feynman was recruited by Robert R. Wilson, who was working on means to produce enriched uranium for use in an atomic bomb, as part of what would become the Manhattan Project. At the time, Feynman had not earned a graduate degree. Wilson's team at Princeton was working on a device called an isotron, intended to electromagnetically separate uranium-235 from uranium-238. This was done in a quite different manner from that used by the calutron that was under development by a team under Wilson's former mentor, Ernest O. Lawrence, at the Radiation Laboratory of the University of California. On paper, the isotron was many times more efficient than the calutron, but Feynman and Paul Olum struggled to determine whether it was practical. Ultimately, on Lawrence's recommendation, the isotron project was abandoned. At this juncture, in early 1943, Robert Oppenheimer was establishing the Los Alamos Laboratory, a secret laboratory on a mesa in New Mexico where atomic bombs


id: richard-feynman-20260505-3
file: data/en.wikipedia.org/wiki/Richard_Feynman-3.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
instance: kb-cron
parent: richard-feynman-20260505-0
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Informed that Arline was dying, Feynman drove to Albuquerque and sat with her for hours until she died on June 16, 1945. He then immersed himself in work on the project and was present at the Trinity nuclear test. Feynman claimed to be the only person to see the explosion without the very dark glasses or welder's lenses provided, reasoning that it was safe to look through a truck windshield, as it would screen out the harmful ultraviolet radiation. The immense brightness of the explosion made him duck to the truck's floor, where he saw a temporary "purple splotch" afterimage. == Cornell (1945–1949) == Feynman nominally held an appointment at the University of Wisconsin–Madison as an assistant professor of physics, but was on unpaid leave during his involvement in the Manhattan Project. In 1945, he received a letter from Dean Mark Ingraham of the College of Letters and Science requesting his return to the university to teach in the coming academic year. His appointment was not extended when he did not commit to returning. In a talk given there several years later, Feynman quipped, "It's great to be back at the only university that ever had the good sense to


id: richard-feynman-20260505-4
file: data/en.wikipedia.org/wiki/Richard_Feynman-4.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
summary:
Feynman was not the only frustrated theoretical physicist in the early post-war years. Quantum electrodynamics suffered from infinite integrals in perturbation theory. These were clear mathematical flaws in the theory, which Feynman and Wheeler had tried, unsuccessfully, to work around. "Theoreticians", noted Murray Gell-Mann, "were in disgrace". In June 1947, leading American physicists met at the Shelter Island Conference. For Feynman, it was his "first big conference with big men ... I had never gone to one like this one in peacetime." The problems plaguing quantum electrodynamics were discussed, but the theoreticians were completely overshadowed by the achievements of the experimentalists, who reported the discovery of the Lamb shift, the measurement of the magnetic moment of the electron, and Robert Marshak's two-meson hypothesis. Bethe took the lead from the work of Hans Kramers, and derived a renormalized non-relativistic quantum equation for the Lamb shift. The next step was to create a relativistic version. Feynman thought that he could do this, but when he went back to Bethe with his solution, it did not converge. Feynman carefully worked through the problem again, applying the path integral formulation that he had used in his thesis. Like Bethe, he made the integral finite


id: richard-feynman-20260505-5
file: data/en.wikipedia.org/wiki/Richard_Feynman-5.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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=== Personal and political life === Feynman did not return to Cornell. Bacher, who had been instrumental in bringing Feynman to Cornell, had lured him to the California Institute of Technology (Caltech). Part of the deal was that he could spend his first year on sabbatical in Brazil. He had become smitten by Mary Louise Bell from Neodesha, Kansas. They had met in a cafeteria in Cornell, where she had studied the history of Mexican art and textiles. She later followed him to Caltech, where he gave a lecture. While he was in Brazil, she taught classes on the history of furniture and interiors at Michigan State University. He proposed to her by mail from Rio de Janeiro, and they married in Boise, Idaho, on June 28, 1952, shortly after he returned. They frequently quarreled and she was frightened by what she described as "a violent temper". Their politics were different; although he registered and voted as a Republican, she was more conservative, and her opinion on the 1954 Oppenheimer security hearing ("Where there's smoke there's fire") offended him. They separated on May 20, 1956. An interlocutory decree of divorce was entered on June 19, 1956, on the grounds of


id: richard-feynman-20260505-6
file: data/en.wikipedia.org/wiki/Richard_Feynman-6.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
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=== Physics === At Caltech, Feynman investigated the physics of the superfluidity of supercooled liquid helium, where helium seems to display a complete lack of viscosity when flowing. Feynman provided a quantum-mechanical explanation for the Soviet physicist Lev Landau's theory of superfluidity. Applying the Schrödinger equation to the question showed that the superfluid was displaying quantum mechanical behavior observable on a macroscopic scale. This helped with the problem of superconductivity, but the solution eluded Feynman. It was solved with the BCS theory of superconductivity, proposed by John Bardeen, Leon Neil Cooper, and John Robert Schrieffer in 1957. Feynman, inspired by a desire to quantize the Wheeler–Feynman absorber theory of electrodynamics, laid the groundwork for the path integral formulation and Feynman diagrams. With Murray Gell-Mann, Feynman developed a model of weak decay, which showed that the current coupling in the process is a combination of vector and axial currents (an example of weak decay is the decay of a neutron into an electron, a proton, and an antineutrino). Although E. C. George Sudarshan and Robert Marshak developed the theory nearly simultaneously, Feynman's collaboration with Gell-Mann was seen as seminal because the weak interaction was neatly described by the vector and axial


id: richard-feynman-20260505-7
file: data/en.wikipedia.org/wiki/Richard_Feynman-7.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
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In the early 1960s, Feynman acceded to a request to "spruce up" the teaching of undergraduates at Caltech. After three years devoted to the task, he produced a series of lectures that later became The Feynman Lectures on Physics. Accounts vary about how successful the original lectures were. Feynman's own preface, written just after an exam on which the students did poorly, was somewhat pessimistic. His colleagues David L. Goodstein and Gerry Neugebauer said later that the intended audience of first-year students found the material intimidating while older students and faculty found it inspirational, so the lecture hall remained full even as the first-year students dropped away. In contrast, physicist Matthew Sands recalled the student attendance as being typical for a large lecture course. Converting the lectures into books occupied Matthew Sands and Robert B. Leighton as part-time co-authors for several years. Feynman suggested that the book cover should have a picture of a drum with mathematical diagrams about vibrations drawn upon it, in order to illustrate the application of mathematics to understanding the world. Instead, the publishers gave the books plain red covers, though they included a picture of Feynman playing drums in the foreword. Even though the books


id: richard-feynman-20260505-8
file: data/en.wikipedia.org/wiki/Richard_Feynman-8.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
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=== Surely You're Joking, Mr. Feynman! === In the 1960s, Feynman began thinking of writing an autobiography, and he began granting interviews to historians. In the 1980s, working with Ralph Leighton (Robert Leighton's son), he recorded chapters on audio tape that Ralph transcribed. The book was published in 1985 as Surely You're Joking, Mr. Feynman! and became a best-seller. Gell-Mann was upset by Feynman's account in the book of the weak interaction work, and threatened to sue, resulting in a correction being inserted in later editions. This incident was just the latest provocation in decades of bad feeling between the two scientists. Gell-Mann often expressed frustration at the attention Feynman received; he remarked: "[Feynman] was a great scientist, but he spent a great deal of his effort generating anecdotes about himself." Feynman has been criticized for a chapter in the book entitled "You Just Ask Them?", where he describes how he learned to seduce women at a bar he went to in the summer of 1946. A mentor taught him to ask a woman if she would sleep with him before buying her anything. He describes seeing women at the bar as "bitches" in his thoughts, and tells a story


id: richard-feynman-20260505-9
file: data/en.wikipedia.org/wiki/Richard_Feynman-9.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
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Aspects of Feynman's life have been portrayed in various media. Feynman was portrayed by Matthew Broderick in the 1996 biopic Infinity. Actor Alan Alda commissioned playwright Peter Parnell to write a two-character play about a fictional day in the life of Feynman set two years before Feynman's death. The play, QED, premiered at the Mark Taper Forum in Los Angeles in 2001 and was later presented at the Vivian Beaumont Theater on Broadway, with both productions starring Alda as Richard Feynman. Real Time Opera premiered its opera Feynman at the Norfolk (Connecticut) Chamber Music Festival in June 2005. In 2011, Feynman was the subject of a biographical graphic novel entitled simply Feynman, written by Jim Ottaviani and illustrated by Leland Myrick. In 2013, Feynman's role on the Rogers Commission was dramatized by the BBC in The Challenger (US title: The Challenger Disaster), with William Hurt playing Feynman. In 2016, Oscar Isaac performed a public reading of Feynman's 1946 love letter to the late Arline. In the 2023 American film Oppenheimer, directed by Christopher Nolan and based on American Prometheus, Feynman is portrayed by actor Jack Quaid. On May 4, 2005, the United States Postal Service issued the "American Scientists" commemorative


id: richard-feynman-20260505-10
file: data/en.wikipedia.org/wiki/Richard_Feynman-10.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
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=== Selected scientific works === Feynman, Richard P. (1942). Laurie M. Brown (ed.). The Principle of Least Action in Quantum Mechanics. PhD Dissertation, Princeton University. World Scientific (with title "Feynman's Thesis: a New Approach to Quantum Theory") (published 2005). ISBN 978-981-256-380-4 Wheeler, John A.; Feynman, Richard P. (1945). "Interaction with the Absorber as the Mechanism of Radiation". Reviews of Modern Physics. 17 (2–3): 157–181. Bibcode:1945RvMP...17..157W. doi:10.1103/RevModPhys.17.157. Archived from the original on April 17, 2020. Retrieved May 20, 2019. Feynman, Richard P. (1946). A Theorem and its Application to Finite Tampers. Los Alamos Scientific Laboratory, Atomic Energy Commission. doi:10.2172/4341197. OSTI 4341197. Feynman, Richard P.; Welton, T. A. (1946). Neutron Diffusion in a Space Lattice of Fissionable and Absorbing Materials. Los Alamos Scientific Laboratory, Atomic Energy Commission. doi:10.2172/4381097. OSTI 4381097. Feynman, Richard P.; Metropolis, N.; Teller, E. (1947). Equations of State of Elements Based on the Generalized Fermi-Thomas Theory (PDF). Los Alamos Scientific Laboratory, Atomic Energy Commission. doi:10.2172/4417654. OSTI 4417654. Feynman, Richard P. (1948). "Space-time approach to non-relativistic quantum mechanics". Reviews of Modern Physics. 20 (2): 367–387. Bibcode:1948RvMP...20..367F. doi:10.1103/RevModPhys.20.367. Archived from the original on September 17, 2020. Retrieved May 20, 2019. Feynman, Richard P. (1948). "A Relativistic Cut-Off for Classical Electrodynamics". Physical


id: richard-feynman-20260505-11
file: data/en.wikipedia.org/wiki/Richard_Feynman-11.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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Feynman, Richard P.; Leighton, Robert B.; Sands, Matthew (2005) [1970]. The Feynman Lectures on Physics: The Definitive and Extended Edition (2nd ed.). Addison Wesley. ISBN 0-8053-9045-6. Includes Feynman's Tips on Physics (with Michael Gottlieb and Ralph Leighton), which includes four previously unreleased lectures on problem solving, exercises by Robert Leighton and Rochus Vogt, and a historical essay by Matthew Sands. Three volumes; originally published as separate volumes in 1964 and 1966. Feynman, Richard P. (1961). Theory of Fundamental Processes. Addison Wesley. Feynman, Richard P. (1962). Quantum Electrodynamics. Addison Wesley. Feynman, Richard P.; Hibbs, Albert (1965). Quantum Mechanics and Path Integrals. McGraw Hill. ISBN 0-07-020650-3. Feynman, Richard P. (1967). The Character of Physical Law: The 1964 Messenger Lectures. MIT Press. ISBN 0-262-56003-8. Feynman, Richard P. (1972). Statistical Mechanics: A Set of Lectures. Reading, Mass: W. A. Benjamin. ISBN 0-8053-2509-3. Feynman, Richard P. (1972). Photon-Hadron interactions. Reading, Mass: W. A. Benjamin. ISBN 0-201-36074-8. Feynman, Richard P. (1985b). QED: The Strange Theory of Light and Matter. Princeton University Press. ISBN 0-691-02417-0. Feynman, Richard P. (1987). Elementary Particles and the Laws of Physics: The 1986 Dirac Memorial Lectures. Cambridge University Press. ISBN 0-521-34000-4. Feynman, Richard P. (1995). Brian Hatfield (ed.). Lectures on Gravitation. Addison


id: richard-feynman-20260505-12
file: data/en.wikipedia.org/wiki/Richard_Feynman-12.md
category: reference
title: Richard Feynman
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Richard_Feynman
date_saved: 2026-05-05T11:07:01.571261+00:00
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parent: richard-feynman-20260505-0
summary:
== Sources == Bashe, Charles J.; Johnson, Lyle R.; Palmer, John H.; Pugh, Emerson W. (1986). IBM's Early Computers. Cambridge, Massachusetts: MIT. ISBN 0-262-02225-7. OCLC 12021988. Bethe, Hans A. (1991). The Road from Los Alamos. Masters of Modern Physics. Vol. 2. New York: Simon and Schuster. ISBN 0-671-74012-1. OCLC 24734608. Brian, Denis (2001). The Voice of Genius: Conversations with Nobel Scientists and Other Luminaries. Cambridge, Massachusetts: Perseus. ISBN 978-0-7382-0447-5. OCLC 751292707. Carroll, John Bissell (1996). Sternberg, Robert J.; Ben-Zeev, Talia (eds.). The Nature of Mathematical Thinking. Mahwah, New Jersey: L. Erlbaum Associates. ISBN 978-0-8058-1799-7. OCLC 34513302. Chown, Marcus (May 2, 1985). "Strangeness and Charm". New Scientist: 34. ISSN 0262-4079. Close, Frank (2011). The Infinity Puzzle: The Personalities, Politics, and Extraordinary Science Behind the Higgs Boson. Oxford University Press. ISBN 978-0-19-959350-7. OCLC 840427493. Deutsch, David (June 1, 1992). "Quantum computation". Physics World. 5 (6): 57–61. doi:10.1088/2058-7058/5/6/38. ISSN 0953-8585. Friedman, Jerome (2004). "A Student's View of Fermi". In Cronin, James W. (ed.). Fermi Remembered. Chicago, Illinois: University of Chicago Press. ISBN 978-0-226-12111-6. OCLC 835230762. Galison, Peter (1998). "Feynman's War: Modelling Weapons, Modelling Nature". Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics. 29 (3):


id: fibonacci-anyons-20260505-0
file: data/en.wikipedia.org/wiki/Fibonacci_anyons-0.md
category: reference
title: Fibonacci anyons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fibonacci_anyons
date_saved: 2026-05-05T11:07:02.742403+00:00
instance: kb-cron
parent: fibonacci-anyons-20260505-0
summary:
In condensed matter physics, a Fibonacci anyon is a type of anyon which lives in two-dimensional topologically ordered systems. The Fibonacci anyon τ {\displaystyle \tau } is distinguished uniquely by the fact that it satisfies the fusion rule τ ⊗ τ = 1 ⊕ τ {\displaystyle \tau \otimes \tau ={\bf {1}}\oplus \tau } . Alternatively, the Fibonacci anyon can be defined by fact that it is algebraically described by the unique non-trivial simple object in the Fibonacci category. Experimentally, it has been proposed that Fibonacci anyons could be hosted in the fractional quantum Hall system. In particular, it is possible that Fibonacci anyons are present in the system with filling factor ν = 12 / 5 {\displaystyle \nu =12/5} . Fibonacci anyons have primary been developed in the context of topological quantum computing. This is because these anyons allow for universal quantum computing based entirely on braiding and performing topological charge measurements, and hence form a natural setting for topological quantum computing. This is in contrast to anyons based on discrete gauge theory, which require a more subtle use of ancillas to perform universal quantum computation. == The Fibonacci category == Mathematically, the Fibonacci anyons are identified by the fact


id: fibonacci-anyons-20260505-1
file: data/en.wikipedia.org/wiki/Fibonacci_anyons-1.md
category: reference
title: Fibonacci anyons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fibonacci_anyons
date_saved: 2026-05-05T11:07:02.742403+00:00
instance: kb-cron
parent: fibonacci-anyons-20260505-0
summary:
== Relationship to topological quantum field theory == In the context of topological quantum field theory, the Fibonacci category corresponds to the quantum Chern–Simons theory with gauge group G = S O ( 3 ) {\displaystyle G=SO(3)} at level k = 5 {\displaystyle k=5} . Seeing as SO ( 3 ) {\displaystyle {\text{SO}}(3)} is a double cover of SU ( 2 ) {\displaystyle {\text{SU}}(2)} , the Fibonacci category can alternatively be described as the even sectors in the Chern–Simons theory with gauge group G = SU ( 2 ) {\displaystyle G={\text{SU}}(2)} at level k = 3 {\displaystyle k=3} . From this perspective, one can see a connection between Fibonacci anyons and the Jones polynomial polynomial using the classical techniques of Edward Witten. In his seminal 1989 paper, Witten demonstrated that the link and manifold invariants of quantum Chern–Simons theory with gauge group G = S U ( 2 ) {\displaystyle G=SU(2)} are related intimately to the Jones polynomial evaluated at roots of unity. Since the Fibonacci category is related to G = SU ( 2 ) {\displaystyle G={\text{SU}}(2)} Chern–Simons theory, this gives a relation between the Fibonacci category and the Jones polynomial. A key insight of Michael Freedman in 1997


id: fibonacci-anyons-20260505-2
file: data/en.wikipedia.org/wiki/Fibonacci_anyons-2.md
category: reference
title: Fibonacci anyons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fibonacci_anyons
date_saved: 2026-05-05T11:07:02.742403+00:00
instance: kb-cron
parent: fibonacci-anyons-20260505-0
summary:
== Method for universal quantum computing == The pipeline for universal quantum computing with Fibonacci anyons can be described as follows. First, one is given an instance of a decision problem which is in the complexity class BQP (for instance, a large integer whose factorization one wishes to determine). Since the problem of additively approximating a normalization of the Jones polynomial at a third root of unity is BQP complete, this means by definition that there is a polynomial time classical algorithm for taking any efficient quantum circuit an assigning to it a framed link such that an additive approximation of the Jones invariant (or really, Kauffman bracket) of that link evaluated at e 3 π i / 5 {\displaystyle e^{3\pi i/5}} encodes the solution of the decision problem. For example, using this procedure, Shor's algorithm for factoring an integer would correspond to some large link. To relate the Kauffman bracket of this link evaluated at e 3 π i / 5 {\displaystyle e^{3\pi i/5}} to the physical world, one would take some material which hosts Fibonacci anyons, and perform a series of creation, braiding, and fusion operators such that the spacetime trajectories of the Fibonacci anyons in this process


id: five-qubit-error-correcting-code-20260505-0
file: data/en.wikipedia.org/wiki/Five-qubit_error_correcting_code-0.md
category: reference
title: Five-qubit error correcting code
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Five-qubit_error_correcting_code
date_saved: 2026-05-05T11:07:03.873413+00:00
instance: kb-cron
parent: five-qubit-error-correcting-code-20260505-0
summary:
The five-qubit error correcting code, [[5,1,3]] code, or Laflamme–Miquel–Paz–Zurek code is the smallest quantum error correcting code that can protect a logical qubit from any arbitrary single qubit error. In this code, 5 physical qubits are used to encode the logical qubit. With X {\displaystyle X} and Z {\displaystyle Z} being Pauli matrices and I {\displaystyle I} the Identity matrix, this code's generators are ⟨ X Z Z X I , I X Z Z X , X I X Z Z , Z X I X Z ⟩ {\displaystyle \langle XZZXI,IXZZX,XIXZZ,ZXIXZ\rangle } . Its logical operators are X ¯ = X X X X X {\displaystyle {\bar {X}}=XXXXX} and Z ¯ = Z Z Z Z Z {\displaystyle {\bar {Z}}=ZZZZZ} . Once the logical qubit is encoded, errors on the physical qubits can be detected via stabilizer measurements. A lookup table that maps the results of the stabilizer measurements to the types and locations of the errors gives the control system of the quantum computer enough information to correct errors. == History == Peter Shor's original quantum error correcting code of 1995 used nine qubits. The five-qubit error correcting code was published independently by two groups in 1996: by


id: fluxonium-20260505-0
file: data/en.wikipedia.org/wiki/Fluxonium-0.md
category: reference
title: Fluxonium
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fluxonium
date_saved: 2026-05-05T11:07:05.111266+00:00
instance: kb-cron
parent: fluxonium-20260505-0
summary:
In quantum computing, the fluxonium is a type of superconducting qubit architecture used for gate-based quantum computation that is insensitive to offset charge noise. It is constructed from a Josephson junction, a capacitor, and a “superinductor” (a type of inductor) arranged in a loop. The fluxonium was first proposed as a candidate for a qubit by an experimental group at Yale University led by Michel Devoret in 2009. It is a flux-like qubit, meaning that its energy levels correspond to integer numbers of magnetic flux/phase states. This architecture has long coherence times and high anharmonicity (or nonlinearity), both of which are important for successful qubit architectures. By changing the relative values of the different circuit components, fluxoniums can be engineered to have other properties, such as resistance to noise. However, the design requires complex fabrication methods, and is therefore difficult to scale. The fluxonium architecture has achieved among the strongest coherence for any solid-state superconducting qubit, with millisecond-level coherence times. Fluxoniums are a candidate for a qubit in a quantum processor, with some companies like D-Wave, Atlantic Quantum, and Qilimanjaro focused specifically on developing fluxonium-based quantum computing hardware. == Background == The first successful superconducting qubits were charge qubits, also


id: google-quantum-ai-20260505-0
file: data/en.wikipedia.org/wiki/Google_Quantum_AI-0.md
category: reference
title: Google Quantum AI
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Google_Quantum_AI
date_saved: 2026-05-05T11:07:06.284469+00:00
instance: kb-cron
parent: google-quantum-ai-20260505-0
summary:
Google Quantum AI is a research division of Google focused on developing quantum computing technologies. Its plan is to build large-scale, error-corrected quantum computers and advance quantum hardware, software, and algorithms for scientific and practical applications beyond the capacities of classical computers. == References ==


id: google-research-20260505-0
file: data/en.wikipedia.org/wiki/Google_Research-0.md
category: reference
title: Google Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Google_Research
date_saved: 2026-05-05T11:07:07.470932+00:00
instance: kb-cron
parent: google-research-20260505-0
summary:
Google Research (also known as Research at Google) is the research division of Google, a subsidiary of Alphabet Inc.. According to its official website, Google Research publishes findings, releases open-source software, and applies research results within Google products and services as well as within the wider scientific community. == Notable contributions == The 2017 landmark paper Attention Is All You Need, which introduced the Transformer architecture, which has subsequently been used to build modern large language models. Advances in neural machine translation powering Google Translate. Time series forecasting. Development of scalable learning systems and infrastructure for large-model training. Flood forecasting. Research into computational discovery via Google Accelerated Science including demonstrating the first below-threshold quantum calculations. == See also == Google AI Google Brain Google DeepMind == References == == External links == Official website Google AI portal


id: gottesman-kitaev-preskill-code-20260505-0
file: data/en.wikipedia.org/wiki/Gottesman–Kitaev–Preskill_code-0.md
category: reference
title: Gottesman–Kitaev–Preskill code
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Gottesman–Kitaev–Preskill_code
date_saved: 2026-05-05T11:07:08.673257+00:00
instance: kb-cron
parent: gottesman-kitaev-preskill-code-20260505-0
summary:
The Gottesman–Kitaev–Preskill (GKP) code is a quantum error correcting code that encodes logical qubits into the continuous degrees of freedom of a quantum system. It is named after Daniel Gottesman, Alexei Kitaev and John Preskill who published it together in 2001. The code is used in continuous variable (CV) photonic quantum computing, in which logical qubits are encoded into the field quadratures of an optical mode. These modes can be thought of as the quantum harmonic oscillator with conjugate position and momentum operators. By encoding logical qubits into a single optical mode, the GKP code demonstrates greater hardware efficiency than traditional qubit codes. Instead of needing many qubits to act as redundancy for a single qubit, the GKP code instead requires a precisely constructed optical state. GKP codes are able to protect against both small shifts in the quadratures, but also loss channels such as photon loss in a photonic system. == Overview == GKP codes protects against random shifts in the quadratures, which can be modeled as a Gaussian random displacement channel. N ( ρ ) = ∫ d x e − | | x | | 2 / 2 σ ~ 2 D ( x ) ρ D


id: gottesman-kitaev-preskill-code-20260505-1
file: data/en.wikipedia.org/wiki/Gottesman–Kitaev–Preskill_code-1.md
category: reference
title: Gottesman–Kitaev–Preskill code
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Gottesman–Kitaev–Preskill_code
date_saved: 2026-05-05T11:07:08.673257+00:00
instance: kb-cron
parent: gottesman-kitaev-preskill-code-20260505-0
summary:
== Experimental realization == Physically, GKP states are realized in the following way. First, cat states are generated via Gaussian boson sampling (GBS) techniques, then, the cat states are squeezed and interfered at a beam splitter. Homodyne detection is performed at one output of the beam splitter, and depending on the outcome, an approximate GKP state is created. The output can be further interfered to produce better approximations Cat states are superpositions of out of phase coherent states. They can be written as | ψ ⟩ = N ( | α ⟩ + e i ϕ | − α ⟩ ) {\displaystyle |\psi \rangle ={\mathcal {N}}(|\alpha \rangle +e^{i\phi }|-\alpha \rangle )} Where N {\displaystyle {\mathcal {N}}} is a normalization factor defined as N = [ 2 + 2 e ( − 2 α 2 ) cos ⁡ ϕ ] − 1 / 2 {\displaystyle {\mathcal {N}}=[2+2e^{(-2\alpha ^{2})}\cos {\phi }]^{-1/2}} . These states can be generated in a variety of ways with varying efficiencies. Photon subtraction is one approach, which uses squeezed vacuum states, beam splitters, and photon number resolving (PNR) detectors. The beam splitters must be tuned with a high transmissivity however, making this process impractical for state preparation. The


id: hadamard-test-20260505-0
file: data/en.wikipedia.org/wiki/Hadamard_test-0.md
category: reference
title: Hadamard test
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hadamard_test
date_saved: 2026-05-05T11:07:09.911487+00:00
instance: kb-cron
parent: hadamard-test-20260505-0
summary:
In quantum computation, the Hadamard test is a method used to create a random variable whose expected value is the expected real part R e ⟨ ψ | U | ψ ⟩ {\displaystyle \mathrm {Re} \langle \psi |U|\psi \rangle } , where | ψ ⟩ {\displaystyle |\psi \rangle } is a quantum state and U {\displaystyle U} is a unitary gate acting on the space of | ψ ⟩ {\displaystyle |\psi \rangle } . The Hadamard test produces a random variable whose image is in { ± 1 } {\displaystyle \{\pm 1\}} and whose expected value is exactly R e ⟨ ψ | U | ψ ⟩ {\displaystyle \mathrm {Re} \langle \psi |U|\psi \rangle } . It is possible to modify the circuit to produce a random variable whose expected value is I m ⟨ ψ | U | ψ ⟩ {\displaystyle \mathrm {Im} \langle \psi |U|\psi \rangle } by applying an S † {\displaystyle S^{\dagger }} gate after the first Hadamard gate. == Description of the circuit == To perform the Hadamard test we first calculate the state 1 2 ( | 0 ⟩ + | 1 ⟩ ) ⊗ | ψ ⟩ {\displaystyle {\frac {1}{\sqrt {2}}}\left(\left|0\right\rangle +\left|1\right\rangle \right)\otimes


id: hamiltonian-quantum-computation-20260505-0
file: data/en.wikipedia.org/wiki/Hamiltonian_quantum_computation-0.md
category: reference
title: Hamiltonian quantum computation
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hamiltonian_quantum_computation
date_saved: 2026-05-05T11:07:11.125771+00:00
instance: kb-cron
parent: hamiltonian-quantum-computation-20260505-0
summary:
Hamiltonian quantum computation is a form of quantum computing. Unlike methods of quantum computation such as the adiabatic, measurement-based and circuit model where eternal control is used to apply operations on a register of qubits, Hamiltonian quantum computers operate without external control. == Background == Hamiltonian quantum computation was the pioneering model of quantum computation, first proposed by Paul Benioff in 1980. Benioff's motivation for building a quantum mechanical model of a computer was to have a quantum mechanical description of artificial intelligence and to create a computer that would dissipate the least amount of energy allowable by the laws of physics. However, his model was not time-independent and local. Richard Feynman, independent of Benioff, also wanted to provide a description of a computer based on the laws of quantum physics. He solved the problem of a time-independent and local Hamiltonian by proposing a continuous-time quantum walk that could perform universal quantum computation. Superconducting qubits, Ultracold atoms and non-linear photonics have been proposed as potential experimental implementations of Hamiltonian quantum computers. == Definition == Given a list of quantum gates described as unitaries U 1 , U 2 . . . U k {\displaystyle U_{1},U_{2}...U_{k}} , define a hamiltonian H


id: hanyuan-1-20260505-0
file: data/en.wikipedia.org/wiki/Hanyuan-1-0.md
category: reference
title: Hanyuan-1
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hanyuan-1
date_saved: 2026-05-05T11:07:12.258464+00:00
instance: kb-cron
parent: hanyuan-1-20260505-0
summary:
Hanyuan-1, or Hanyuan No. 1, is China's first quantum computer. It was developed by the Chinese Academy of Sciences’ Innovation Academy for Precision Measurement Science and Technology. It is able to operate at room temperature and uses cold atoms as qubits. It is commercially available with current orders totalling 40 million yuan. The Hanyuan-1 contains 100 qubits. It can fit within three standard equipment racks, and can manage complex applications in the area of logistics optimization and financial modeling. == References ==


id: hidden-subgroup-problem-20260505-0
file: data/en.wikipedia.org/wiki/Hidden_subgroup_problem-0.md
category: reference
title: Hidden subgroup problem
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hidden_subgroup_problem
date_saved: 2026-05-05T11:07:13.896259+00:00
instance: kb-cron
parent: hidden-subgroup-problem-20260505-0
summary:
The hidden subgroup problem (HSP) is a topic of research in mathematics and theoretical computer science. It is a generalization of problems including factoring, discrete logarithm, graph isomorphism, and the shortest vector problem. This makes it especially important in the theory of quantum computing because Shor's algorithms for factoring and finding discrete logarithms in quantum computing are instances of the hidden subgroup problem for finite abelian groups, while the other problems correspond to finite groups that are not abelian. == Problem statement == Given a group G {\displaystyle G} , a subgroup H ≤ G {\displaystyle H\leq G} , and a set X {\displaystyle X} , we say a function f : G → X {\displaystyle f:G\to X} hides the subgroup H {\displaystyle H} if for all g 1 , g 2 ∈ G , f ( g 1 ) = f ( g 2 ) {\displaystyle g_{1},g_{2}\in G,f(g_{1})=f(g_{2})} if and only if g 1 H = g 2 H {\displaystyle g_{1}H=g_{2}H} . Equivalently, f {\displaystyle f} is constant on each coset of H, while it is different between the different cosets of H. Hidden subgroup problem: Let G {\displaystyle G} be a group, X {\displaystyle X} a finite set,


id: hidden-subgroup-problem-20260505-1
file: data/en.wikipedia.org/wiki/Hidden_subgroup_problem-1.md
category: reference
title: Hidden subgroup problem
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hidden_subgroup_problem
date_saved: 2026-05-05T11:07:13.896259+00:00
instance: kb-cron
parent: hidden-subgroup-problem-20260505-0
summary:
==== Procedure ==== The set of characters of G {\displaystyle G} forms a group G ^ {\displaystyle {\widehat {G}}} called the dual group of G {\displaystyle G} . We also have a subgroup H ⊥ ≤ G ^ {\displaystyle H^{\perp }\leq {\widehat {G}}} of size | G | / | H | {\displaystyle |G|/|H|} defined by H ⊥ = { χ g : χ g ( h ) = 1 for all h ∈ H } {\displaystyle H^{\perp }=\{\chi _{g}:\chi _{g}(h)=1{\text{ for all }}h\in H\}} For each iteration of the algorithm, the quantum circuit outputs an element g ∈ G {\displaystyle g\in G} corresponding to a character χ g ∈ H ⊥ {\displaystyle \chi _{g}\in H^{\perp }} , and since χ g ( h ) = 1 {\displaystyle \chi _{g}(h)={1}} for all h ∈ H {\displaystyle h\in H} , it helps to pin down what H {\displaystyle H} is. The algorithm is as follows: Start with the state | 0 ⟩ | 0 ⟩ {\displaystyle |0\rangle |0\rangle } , where the left register's basis states are each element of G {\displaystyle G} , and the right register's basis states are each element of X {\displaystyle X} . Create a superposition


id: horse-ridge-chip-20260505-0
file: data/en.wikipedia.org/wiki/Horse_Ridge_(chip)-0.md
category: reference
title: Horse Ridge (chip)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Horse_Ridge_(chip)
date_saved: 2026-05-05T11:07:15.088356+00:00
instance: kb-cron
parent: horse-ridge-chip-20260505-0
summary:
Intel "Horse Ridge" is a cryogenic control chip that presented at the International Solid State Circuits Conference 2020 of San Francisco. Horse Ridge is based on Intel's 22nm FFL (FinFET Low Power) CMOS technology. Intel and QuTech published a study in Nature in which they demonstrate that they have been able to operate qubits at temperatures above 1 degree Kelvin (-272.15 degrees Celsius). In December 2020, Intel released Horse Ridge II, adding enhanced capabilities and higher levels of integration for sophisticated control of the quantum system. New features include the ability to manipulate and read qubit states (and drive up to 16 spin qubits with a direct digital synthesis (DDS) architecture) and control the potential of multiple gates needed to correlate multiple qubits (features 22 high-speed digital-to-analog converters (DACs)). Horse Ridge II is also implemented using Intel's low-power 22 nm FinFET technology (22FFL) and its operation has been tested at a temperature of 4 degree Kelvin. == References ==


id: elanor-huntington-20260505-0
file: data/en.wikipedia.org/wiki/Elanor_Huntington-0.md
category: reference
title: Elanor Huntington
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Elanor_Huntington
date_saved: 2026-05-05T11:07:16.224202+00:00
instance: kb-cron
parent: elanor-huntington-20260505-0
summary:
Elanor H. Huntington is an Australian scientist and engineer who is Deputy Chief Executive at the Commonwealth Scientific and Industrial Research Organisation and a professor of Quantum Cybernetics at the Australian National University. She led a research program in the Australian Research Council Centre of Excellence for Quantum Computation and Communication Technology. == Early life and education == Huntington studied physics at the Australian National University and graduated in 1996 with a University Medal. She decided that she enjoyed using science to help others, and switched to engineering. She earned her PhD in 1999 working in experimental quantum optics. Huntington joined the Australian Defence Science and Technology Organisation after graduating, where she worked for 18 months before joining the University of New South Wales Canberra at the Australian Defence Force Academy. == Research == Huntington specialises in high speed measurements and the generation of non-classical states. She works on quantum computation, creating optical microchips that can detect, generate and manipulate states of light. She is interested in the intersection of quantum theory and applications. She joined the University of New South Wales in 2000. She has worked in the School of Engineering and Information Technology at the Australian Defence Force


id: ibm-condor-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Condor-0.md
category: reference
title: IBM Condor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Condor
date_saved: 2026-05-05T11:07:17.441239+00:00
instance: kb-cron
parent: ibm-condor-20260505-0
summary:
IBM Condor is a 1,121-qubit quantum processor created by IBM, unveiled during the IBM Quantum Summit 2023, which occurred on December 4, 2023. It is the 2nd largest quantum processor (in terms of qubits), just shy of the 1,125-qubit quantum processor by the company Atom, created in October 2023. It has a similar performance to its predecessor, the IBM Osprey. It has a 50% increase in qubit density compared to the IBM Osprey, and over a mile of high-density cryogenic flex IO wiring. It is not as fast as the IBM Heron, unveiled during the same event. == References ==


id: ibm-eagle-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Eagle-0.md
category: reference
title: IBM Eagle
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Eagle
date_saved: 2026-05-05T11:07:18.628984+00:00
instance: kb-cron
parent: ibm-eagle-20260505-0
summary:
IBM Eagle is a 127-qubit quantum processor. IBM claims that it can not be simulated by any classical computer. It is two times bigger than China's Jiuzhang 2. It was revealed on November 16, 2021, and was claimed to be the most powerful quantum processor ever made until November 2022, when the IBM Osprey overtook it with 433 qubits. It is almost twice as powerful as their last processor, the 'Hummingbird', which had 65 quantum bits and was created in 2020. IBM believes that the processes used in creating the 'Eagle', will be the backbone for their future processors. == References == == External links == IBM’s roadmap for scaling quantum technology


id: ibm-heron-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Heron-0.md
category: reference
title: IBM Heron
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Heron
date_saved: 2026-05-05T11:07:19.792248+00:00
instance: kb-cron
parent: ibm-heron-20260505-0
summary:
IBM Heron is a 156-qubit tunable-coupler quantum processor created by IBM, originally unveiled during the IBM Quantum Summit 2023, which occurred on December 4, 2023, and is the highest performance quantum processor IBM has ever built. It is currently in use on the IBM Quantum System Two, unveiled during the same event. IBM claims that this processor eliminates cross-talk errors that emerged in their previous quantum processors, and that this processor is being made available for users via the cloud. The first version is reportedly 5 times faster than their previous best record set by the IBM Eagle. == IBM Heron r2 == During the IBM Quantum Developer Conference, a second revision (called r2) was released, which increased the qubit count from 133 to 156, and introduced a two-level system mitigation to reduce the impact of an important source of noise. == References ==


id: ibm-osprey-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Osprey-0.md
category: reference
title: IBM Osprey
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Osprey
date_saved: 2026-05-05T11:07:20.943188+00:00
instance: kb-cron
parent: ibm-osprey-20260505-0
summary:
IBM Osprey is a 433-qubit quantum processor created by IBM, revealed during the IBM Quantum Summit 2022, which occurred on November 9, 2022, in New York, United States. It is 3 times larger than its predecessor, the IBM Eagle. It needs to be cooled down to a temperature of ~0.02 K (-273.13 °C). == References ==


id: ibm-q-system-one-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Q_System_One-0.md
category: reference
title: IBM Q System One
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Q_System_One
date_saved: 2026-05-05T11:07:22.201870+00:00
instance: kb-cron
parent: ibm-q-system-one-20260505-0
summary:
IBM Quantum System One is the first circuit-based commercial quantum computer, introduced by IBM in January 2019. This integrated quantum computing system is housed in an airtight borosilicate glass cube that maintains a controlled physical environment. Each face of the cube is 9 feet (2.7 m) wide and tall. A cylindrical protrusion from the center of the ceiling is a dilution refrigerator, containing a 20-qubit transmon quantum processor. It was tested for the first time in the summer of 2018, for two weeks, in Milan, Italy. IBM Quantum System One was developed by IBM Research, with assistance from the Map Project Office and Universal Design Studio. CERN, ExxonMobil, Fermilab, Argonne National Laboratory, and Lawrence Berkeley National Laboratory are among the clients signed up to access the system remotely. From April 6 to May 31, 2019, the Boston Museum of Science hosted an exhibit featuring a replica of the IBM Quantum System One. On June 15, 2021, IBM deployed the first unit of Quantum System One in Germany at its headquarters in Ehningen. On April 5, 2024, IBM unveiled a Quantum System One at the Rensselaer Polytechnic Institute, the first IBM quantum system on a university campus. == See also ==


id: ibm-q-system-two-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Q_System_Two-0.md
category: reference
title: IBM Q System Two
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Q_System_Two
date_saved: 2026-05-05T11:07:23.407768+00:00
instance: kb-cron
parent: ibm-q-system-two-20260505-0
summary:
IBM Quantum System Two is the first modular utility-scaled quantum computer system, unveiled by IBM on December 4, 2023. It is a successor to the IBM Quantum System One. It contains three IBM Quantum Heron processors, which can be scaled up due to its modularity, and later upgraded for newer quantum processing units, as it is upgradeable. For its maximum efficiency, it has to be cooled to a temperature of a few hundredths of degrees above absolute zero (10–20 mK), using dilution technology. == Current usage == IBM has stated that their clients and partners are using their 100+ qubit systems to advance science. == Future == IBM has stated that their quantum coupling technology will allow multiple Quantum System Two units to connect together, to create systems capable of running 100 million operations in a single quantum circuit, and later a billion operations, by 2033. == References ==


id: ibm-quantum-platform-20260505-0
file: data/en.wikipedia.org/wiki/IBM_Quantum_Platform-0.md
category: reference
title: IBM Quantum Platform
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IBM_Quantum_Platform
date_saved: 2026-05-05T11:07:24.589299+00:00
instance: kb-cron
parent: ibm-quantum-platform-20260505-0
summary:
IBM Quantum Platform (previously known as IBM Quantum Experience) is an online platform allowing public and premium access to cloud-based quantum computing services provided by IBM. This includes access to a set of IBM's quantum processors, a set of tutorials on quantum computation, and access to interactive courses. As of June 2025, there are 12 devices on the service, all of which are freely accessible by the public. This service can be used to run algorithms and experiments, and explore tutorials and simulations around what might be possible with quantum computing. IBM's quantum processors are made up of superconducting transmon qubits, located in dilution refrigerators at the IBM Research headquarters at the Thomas J. Watson Research Center. Users interact with a quantum processor through the quantum circuit model of computation, typically through code written in Qiskit. This code can be compiled down to OpenQASM for execution on real quantum systems. Circuits can be created either graphically with the Quantum Composer, or programmatically through Jupyter notebooks on IBM's approved platforms for cloud-based quantum computing: qBraid and OVHCloud. == History == The service was launched in May 2016 as the IBM Quantum Experience with a five-qubit quantum processor and matching simulator connected


id: illinois-quantum-and-microelectronics-park-20260505-0
file: data/en.wikipedia.org/wiki/Illinois_Quantum_and_Microelectronics_Park-0.md
category: reference
title: Illinois Quantum and Microelectronics Park
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Illinois_Quantum_and_Microelectronics_Park
date_saved: 2026-05-05T11:07:25.761440+00:00
instance: kb-cron
parent: illinois-quantum-and-microelectronics-park-20260505-0
summary:
The Illinois Quantum and Microelectronics Park (IQMP) is a planned 128-acre technology campus on the site of the former U.S. Steel South Works on the south side of Chicago. It will focus on quantum computing and is not an AI data center. Plans for the IQMP are part of the larger “Quantum Shore Chicago” redevelopment of the former U.S. Steel South Works site, a long-vacant industrial area in Chicago’s South Shore neighborhood. The broader project is expected to include advanced manufacturing facilities, research centers, housing, and a replacement hospital, with an initial phase estimated at about $9 billion in investment. The overall park is expected to cost $9 billion to construct. Work is expected to begin in 2026 and be complete in 2028. == Tenants == PsiQuantum of Palo Alto, California has been announced as the anchor tenant of the IQMP, PsiQuantum intends to build and deploy America’s first million-qubit scale, fault-tolerant quantum computer. Other tenants include the DARPA-Illinois Quantum Proving Ground, IBM, Diraq, Quantum Machines, and Infleqtion. French quantum computing company Pasqal will invest more than $65 million to build its U.S. headquarters there. == History == President of Cook County Board of Commissioners Toni Preckwinkle, Chicago Mayor Brandon


id: india-s-quantum-computer-20260505-0
file: data/en.wikipedia.org/wiki/India's_quantum_computer-0.md
category: reference
title: India's quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/India's_quantum_computer
date_saved: 2026-05-05T11:07:26.974850+00:00
instance: kb-cron
parent: india-s-quantum-computer-20260505-0
summary:
India's quantum computer is the proposed and planned quantum computer to be developed in India by 2026. A quantum computer is a computer based on quantum phenomena and governed by the principles of quantum mechanics in physics. The development in the field of quantum computing in the world is also intricately linked to India. The legacy of quantum computing in India can be traced back from the period of Indian theoretical physicist Satyendra Nath Bose. His last four publication on quantum statistics and condensed matter physics led to the foundation of quantum mechanics. It was published in the year 1924. The first quantum computer India launch was of 7 qubits developed at Tata Institute of Fundamental Research, Mumbai. In April 2025, An Indian startup named QpiAi unveiled a 25 qubit Quantum Computer named Indus, this quantum computer launched, is the first full-stack quantum computing system in the country selected under National Quantum Mission India (NQM), Government of India scheme. In the next five years, it is expected that India will invest around one billion dollars in the programs related to the development of the quantum computer. The Government of India has launched an initiative called as National Quantum Mission to


id: india-s-quantum-computer-20260505-1
file: data/en.wikipedia.org/wiki/India's_quantum_computer-1.md
category: reference
title: India's quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/India's_quantum_computer
date_saved: 2026-05-05T11:07:26.974850+00:00
instance: kb-cron
parent: india-s-quantum-computer-20260505-0
summary:
== Research and development == The Ministry of Electronics and Information Technology (MeitY) in collaboration with Amazon Web Services (AWS) established a Quantum Computing Applications Lab to facilitate research and development related to quantum computing in the month of January in 2021. Similarly in the month of March, the Department of Science and Technology (Government of India) and 13 research groups from the Indian Institute of Science Education and Research (IISER) launched I-HUB Quantum Technology Foundation (I-HUB QTF) at Pune for the development of quantum technologies. On the 22nd day of the same month, the Indian Space Research Organisation (ISRO) successfully demonstrated free-space Quantum Communication over a distance of 300 metre. A number of indigenous key technologies were developed to achieve it. It used the indigenous NAVIC receiver for time synchronization between the transmitter and receiver modules, and gimbal mechanism systems. A live videoconferencing was demonstrated using Quantum Key Distribution (QKD) link. It was demonstrated at the campus of Space Applications Centre (SAC) in Ahmedabad. The demonstration was between the two line-of-sight buildings within the campus. It was conducted at night to prevent the interference of the direct sunlight in the demonstration. The experiment is considered as a major achievement


id: india-s-quantum-computer-20260505-2
file: data/en.wikipedia.org/wiki/India's_quantum_computer-2.md
category: reference
title: India's quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/India's_quantum_computer
date_saved: 2026-05-05T11:07:26.974850+00:00
instance: kb-cron
parent: india-s-quantum-computer-20260505-0
summary:
== Startups companies == In the race of the development of quantum technologies, some startups companies in India are emerging to boost research and development projects of quantum computing in India. Bangalore based startup company QpiAI was founded in 2019 for advancements in quantum computing and generative AI technologies. It was founded by Nagendra Nagaraja who is presently the CEO of the company. The company has planned to establish a 25-qubit quantum computer at its headquarter in Bangalore very soon within this year. Similarly another quantum computing startup company BosonQ Psi was also established in Bangalore. It is a simulation software company utilizing quantum computing. It was named after the famous Indian quantum physicist Satyendra Nath Bose and the fundamental quantity Psi. It is also onboard with the US-based IT company IBM's quantum networks. The Government of India under its two flagship initiatives National Quantum Mission and National Mission on Interdisciplinary Cyber-Physical Systems has selected eight major startups companies for innovation of advanced technologies in the areas of quantum computing, communication, sensing, and advanced materials. These eight major startups companies are QNu Labs (Bengaluru), QPiAI India Private Limited (Bengaluru), Dimira Technologies Private Limited (IIT Mumbai), Prenishq Private Limited (IIT Delhi),


id: integrated-quantum-photonics-20260505-0
file: data/en.wikipedia.org/wiki/Integrated_quantum_photonics-0.md
category: reference
title: Integrated quantum photonics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Integrated_quantum_photonics
date_saved: 2026-05-05T11:07:28.243511+00:00
instance: kb-cron
parent: integrated-quantum-photonics-20260505-0
summary:
Integrated quantum photonics, uses photonic integrated circuits to control photonic quantum states for applications in quantum technologies. As such, integrated quantum photonics provides a promising approach to the miniaturisation and scaling up of optical quantum circuits. The major application of integrated quantum photonics is Quantum technology:, for example quantum computing, quantum communication, quantum simulation, quantum walks and quantum metrology. == History == Linear optics was not seen as a potential technology platform for quantum computation until the seminal work of Knill, Laflamme, and Milburn, which demonstrated the feasibility of linear optical quantum computers using detection and feed-forward to produce deterministic two-qubit gates. Following this there were several experimental proof-of-principle demonstrations of two-qubit gates performed in bulk optics. It soon became clear that integrated optics could provide a powerful enabling technology for this emerging field. Early experiments in integrated optics demonstrated the feasibility of the field via demonstrations of high-visibility non-classical and classical interference. Typically, linear optical components such as directional couplers (which act as beamsplitters between waveguide modes), and phase shifters to form nested Mach–Zehnder interferometers are used to encode a qubit in the spatial degree of freedom. That is, a single photon is in superposition between two waveguides, where


id: integrated-quantum-photonics-20260505-1
file: data/en.wikipedia.org/wiki/Integrated_quantum_photonics-1.md
category: reference
title: Integrated quantum photonics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Integrated_quantum_photonics
date_saved: 2026-05-05T11:07:28.243511+00:00
instance: kb-cron
parent: integrated-quantum-photonics-20260505-0
summary:
=== Silicon === A big advantage of using silicon is that the circuits can be tuned actively using integrated thermal microheaters or p-i-n modulators, after the devices have been fabricated. The other big benefit of silicon is its compatibility with CMOS technology, which allows leveraging the mature fabrication infrastructure of the semiconductor electronics industry. The structures differ from modern electronic ones, however, as they are readily scalable. Silicon has a really high refractive index of ~3.5 at the 1550 nm wavelength commonly used in optical telecommunications. It therefore offers one of the highest component densities in integrated photonics. The large contrast in refractive index with glass (1.44) allows waveguides formed of silicon surrounded by glass to have very tight bends, which allows for a high component density and reduced system size. Large silicon-on-insulator (SOI) wafers up to 300 mm in diameter can be obtained commercially, making the technology both available and reproducible. Many of the largest systems (up to several hundred components) have been demonstrated on the silicon photonics platform, with up to eight simultaneous photons, generation of graph states (cluster states), and up to 15 dimensional qubits). Photon sources in silicon waveguide circuits leverage silicon's third-order nonlinearity to produce


id: intelligence-advanced-research-projects-activity-20260505-0
file: data/en.wikipedia.org/wiki/Intelligence_Advanced_Research_Projects_Activity-0.md
category: reference
title: Intelligence Advanced Research Projects Activity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Intelligence_Advanced_Research_Projects_Activity
date_saved: 2026-05-05T11:07:29.453328+00:00
instance: kb-cron
parent: intelligence-advanced-research-projects-activity-20260505-0
summary:
The Intelligence Advanced Research Projects Activity (IARPA) is an organization, within the Office of the Director of National Intelligence (ODNI), that is responsible for leading research to overcome difficult challenges facing the United States Intelligence Community. IARPA characterizes its mission as follows: "To envision and lead high-risk, high-payoff research that delivers innovative technology for future overwhelming intelligence advantage." IARPA funds academic and industry research across a broad range of technical areas, including mathematics, computer science, physics, chemistry, biology, neuroscience, linguistics, political science, and cognitive psychology. Most IARPA research is unclassified and openly published. IARPA transfers successful research results and technologies to other government agencies. Notable IARPA investments include quantum computing, superconducting computing, machine learning, and forecasting tournaments. == Mission == IARPA characterizes its mission as "to envision and lead high-risk, high-payoff research that delivers innovative technology for future overwhelming intelligence advantage". == History == In 1958, the first Advanced Research Projects Agency, or ARPA, was created in response to an unanticipated surprise—the Soviet Union's successful launch of Sputnik on October 4, 1957. The ARPA model was designed to anticipate and pre-empt such technological surprises. As then-Secretary of Defense Neil McElroy said, "I want an agency that makes sure no important


id: intelligence-advanced-research-projects-activity-20260505-1
file: data/en.wikipedia.org/wiki/Intelligence_Advanced_Research_Projects_Activity-1.md
category: reference
title: Intelligence Advanced Research Projects Activity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Intelligence_Advanced_Research_Projects_Activity
date_saved: 2026-05-05T11:07:29.453328+00:00
instance: kb-cron
parent: intelligence-advanced-research-projects-activity-20260505-0
summary:
=== Past research === Aggregative Contingent Estimation (ACE) Program aimed "to dramatically enhance the accuracy, precision, and timeliness of intelligence forecasts for a broad range of event types, through the development of advanced techniques that elicit, weight, and combine the judgments of many intelligence analysts." ATHENA Program was a research program about cybersecurity. It aimed "to provide an early warning system for detecting precursors to cyberattacks". Babel Program developed "agile and robust speech recognition technology that can be rapidly applied to any human language in order to provide effective search capability for analysts to efficiently process massive amounts of real-world recorded speech". The program tried to develop software that could transcribe and search among all the languages. Biometrics Exploitation Science & Technology (BEST) Program focused on trying to "significantly advance the state-of-the-science for biometrics technologies". It was to discover techniques on utilizing biometrics from a subject in a less controlled environment which could produce a similar result to that in a controlled environment. Synthetic Holographic Observation (SHO) Program's stated goal was "to enable full-parallax, full-color, high-resolution display of dynamic 3D data without head-gear, and possessing visually continuous perspectives without artifacts over wide viewing angles." === Current research === Creation of


id: ionq-20260505-0
file: data/en.wikipedia.org/wiki/IonQ-0.md
category: reference
title: IonQ
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IonQ
date_saved: 2026-05-05T11:07:30.727625+00:00
instance: kb-cron
parent: ionq-20260505-0
summary:
IonQ, Inc. is an American quantum computing hardware and software company headquartered in College Park, Maryland. The company develops general-purpose trapped ion quantum computers and accompanying software to generate, optimize, and execute quantum circuits. == History == IonQ was co-founded by Christopher Monroe and Jungsang Kim, professors at Duke University, in 2015, with the help of venture firm New Enterprise Associates. The company is an offshoot of the co-founders’ 25 years of academic research in quantum information science. Monroe's quantum computing research began as a Staff Researcher at the National Institute of Standards and Technology (NIST) with physicist David Wineland where he led a team using trapped ions to produce the first controllable qubits and the first controllable quantum logic gate, culminating in a proposed architecture for a large-scale trapped ion computer. Kim and Monroe, who was at the time a professor at the University of Maryland, College Park (UMD), began collaborating formally as a result of larger research initiatives funded by the Intelligence Advanced Research Projects Activity (IARPA). They wrote a review paper for Science Magazine entitled Scaling the Ion Trap Quantum Processor, pairing Monroe's research at UMD in trapped ions with Kim's focus on scalable quantum information processing


id: iqm-quantum-computers-20260505-0
file: data/en.wikipedia.org/wiki/IQM_Quantum_Computers-0.md
category: reference
title: IQM Quantum Computers
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/IQM_Quantum_Computers
date_saved: 2026-05-05T11:07:31.919551+00:00
instance: kb-cron
parent: iqm-quantum-computers-20260505-0
summary:
IQM Quantum Computers is a Finnish quantum computing hardware and software company headquartered in Espoo, Finland. The company develops and commercializes quantum computers based on superconducting technology. Their goal is to become the leading European company in quantum computing hardware. == Funding == IQM Quantum Computers has secured a total of over €600 million in capital as of 2025, ranking among the most highly funded quantum computing companies in Europe. The company announced a €275 million Series B round in September 2025. This round was led by Ten Eleven Ventures, a U.S.-based cybersecurity-focused investment firm, and Tesi, Finland's state-owned investment fund. It was the largest quantum computing funding round in Europe and the fourth largest round ever for a Finnish growth company to date. The Series B round attracted a diverse group of investors, including Finnish pension funds such as Elo Mutual and Varma Mutual Pension Insurance, the European Innovation Council (EIC). Previous major private funding rounds included a €128 million Series A2 round in 2022 led by World Fund, which brought additional international capital and advanced the company's R&D and scaling activities. Other early investors have included Maki.vc, OpenOcean, MIG Funds, Vito Ventures, and Matadero QED. Public and governmental


id: jiuzhang-quantum-computer-20260505-0
file: data/en.wikipedia.org/wiki/Jiuzhang_(quantum_computer)-0.md
category: reference
title: Jiuzhang (quantum computer)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Jiuzhang_(quantum_computer)
date_saved: 2026-05-05T11:07:33.045556+00:00
instance: kb-cron
parent: jiuzhang-quantum-computer-20260505-0
summary:
Jiuzhang (Chinese: 九章) is the first photonic quantum computer to claim quantum supremacy. Previously quantum supremacy has been achieved only once, in 2019, by Google's Sycamore; however, Google's computer was based on superconducting materials, and not photons. Jiuzhang was developed by a team from University of Science and Technology of China (USTC) led by Pan Jianwei and Lu Chao-Yang. The computer is named after Jiuzhang suanshu, an ancient Chinese mathematical classic book. On 3 December 2020, USTC announced in Science that Jiuzhang successfully performed Gaussian boson sampling in 200 seconds (3 minutes 20 seconds), with a maximum of 76 detected photons. The USTC group estimated that it would take 2.5 billion years for the Sunway TaihuLight supercomputer to perform the same calculation. == Experimental setup == The setup involves a Verdi-pumped Mira 900 Ti:sapphire laser which is split into 13 paths of equal intensity and then shone on 25 PPKTP crystals to produce 25 two-mode squeezed states. Through a hybrid encoding this is equivalent to 50 single-mode squeezed states. The purity is increased from 98% to 99% by 12 nm filtering. The 50 single-mode squeezed states are sent into a 100-mode interferometer and sampled by 100 single-photon detectors with an


id: kane-quantum-computer-20260505-0
file: data/en.wikipedia.org/wiki/Kane_quantum_computer-0.md
category: reference
title: Kane quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Kane_quantum_computer
date_saved: 2026-05-05T11:07:34.231560+00:00
instance: kb-cron
parent: kane-quantum-computer-20260505-0
summary:
The Kane quantum computer is a proposal for a scalable quantum computer proposed by Bruce Kane in 1998, who was then at the University of New South Wales. Often thought of as a hybrid between quantum dot and nuclear magnetic resonance (NMR) quantum computers, the Kane computer is based on an array of individual phosphorus donor atoms embedded in a pure silicon lattice. Both the nuclear spins of the donors and the spins of the donor electrons participate in the computation. Unlike many quantum computation schemes, the Kane quantum computer is in principle scalable to an arbitrary number of qubits. This is possible because qubits may be individually addressed by electrical means. == Description == The original proposal calls for phosphorus donors to be placed in an array with a spacing of 20 nm, approximately 20 nm below the surface. An insulating oxide layer is grown on top of the silicon. Metal A gates are deposited on the oxide above each donor, and J gates between adjacent donors. The phosphorus donors are isotopically pure 31P, which have a nuclear spin of 1/2. The silicon substrate is isotopically pure 28Si which has nuclear spin 0. Using the nuclear spin of the


id: g-peter-lepage-20260505-0
file: data/en.wikipedia.org/wiki/G._Peter_Lepage-0.md
category: reference
title: G. Peter Lepage
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/G._Peter_Lepage
date_saved: 2026-05-05T11:07:35.424839+00:00
instance: kb-cron
parent: g-peter-lepage-20260505-0
summary:
G. Peter Lepage (born 13 April 1952) is a Canadian American theoretical physicist and an academic administrator. He was the Harold Tanner Dean of the College of Arts and Sciences at Cornell University from 2003 to 2013. == Early life and education == Gerard Peter Lepage was born in Canada in 1952. Lepage studied at McGill University and graduated with a bachelor's degree in honours physics in 1972 and the University of Cambridge with a master's degree (M.A.St - Part III of the Mathematical Tripos) in 1973. In 1978, he received his PhD in theoretical physics from Stanford University. == Academic career == Lepage was a research associate at the Stanford Linear Accelerator Center in 1978. He was a postdoctoral research associate at the Laboratory of Nuclear Studies, Cornell University from 1978 to 1980. In 1980, he joined the physics faculty at Cornell University where he became a professor. He received academic tenure in 1984 after only four years on the university faculty. From 1999 to 2003, he was the chair of Cornell's physics department. He was appointed the Harold Tanner Dean of the College of Arts and Sciences, serving from 2003 to 2013. He is a Fellow of the


id: list-of-proposed-quantum-registers-20260505-0
file: data/en.wikipedia.org/wiki/List_of_proposed_quantum_registers-0.md
category: reference
title: List of proposed quantum registers
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_proposed_quantum_registers
date_saved: 2026-05-05T11:07:36.666347+00:00
instance: kb-cron
parent: list-of-proposed-quantum-registers-20260505-0
summary:
A practical quantum computer must use a physical system as a programmable quantum register. Researchers are exploring several technologies as candidates for reliable qubit implementations. Superconducting quantum computing (qubit implemented by the state of nonlinear resonant superconducting circuits containing Josephson junctions) Trapped ion quantum computer (qubit implemented by the internal state of trapped ions) Neutral atom quantum computer (qubit implemented by internal states of neutral atoms trapped in an optical lattice or an array of dipole traps, i.e. optical tweezers) Quantum dot computer, spin-based (e.g. the Loss-DiVincenzo quantum computer) (qubit given by the spin states of trapped electrons) Quantum dot computer, spatial-based (qubit given by electron position in double quantum dot) Quantum computing using engineered quantum wells, which could in principle enable the construction of a quantum computer that operates at room temperature Coupled quantum wire (qubit implemented by a pair of quantum wires coupled by a quantum point contact) Nuclear magnetic resonance quantum computer (NMRQC) implemented with the nuclear magnetic resonance of molecules in solution, where qubits are provided by nuclear spins within the dissolved molecule and probed with radio waves Solid-state NMR Kane quantum computer (qubit realized by the nuclear spin state of phosphorus donors in silicon) Vibrational


id: list-of-quantum-logic-gates-20260505-0
file: data/en.wikipedia.org/wiki/List_of_quantum_logic_gates-0.md
category: reference
title: List of quantum logic gates
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_quantum_logic_gates
date_saved: 2026-05-05T11:07:38.104837+00:00
instance: kb-cron
parent: list-of-quantum-logic-gates-20260505-0
summary:
In gate-based quantum computing, various sets of quantum logic gates are commonly used to express quantum operations. The following tables list several unitary quantum logic gates, together with their common name, how they are represented, and some of their properties. Controlled or conjugate transpose (adjoint) versions of some of these gates may not be listed. == Identity gate and global phase == The identity gate is the identity operation I | ψ ⟩ = | ψ ⟩ {\displaystyle I|\psi \rangle =|\psi \rangle } , most of the times this gate is not indicated in circuit diagrams, but it is useful when describing mathematical results. It has been described as being a "wait cycle", and a NOP. The global phase gate introduces a global phase e i φ {\displaystyle e^{i\varphi }} to the whole qubit quantum state. A quantum state is uniquely defined up to a phase. Because of the Born rule, a phase factor has no effect on a measurement outcome: | e i φ | = 1 {\displaystyle |e^{i\varphi }|=1} for any φ {\displaystyle \varphi } . Because e i δ | ψ ⟩ ⊗ | ϕ ⟩ = e i δ ( | ψ ⟩ ⊗ | ϕ


id: list-of-quantum-logic-gates-20260505-1
file: data/en.wikipedia.org/wiki/List_of_quantum_logic_gates-1.md
category: reference
title: List of quantum logic gates
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_quantum_logic_gates
date_saved: 2026-05-05T11:07:38.104837+00:00
instance: kb-cron
parent: list-of-quantum-logic-gates-20260505-0
summary:
The rotation operator gates R x ( θ ) , R y ( θ ) {\displaystyle R_{x}(\theta ),R_{y}(\theta )} and R z ( θ ) {\displaystyle R_{z}(\theta )} are the analog rotation matrices in three Cartesian axes of SO(3), along the x, y or z-axes of the Bloch sphere projection. As Pauli matrices are related to the generator of rotations, these rotation operators can be written as matrix exponentials with Pauli matrices in the argument. Any 2 × 2 {\displaystyle 2\times 2} unitary matrix in SU(2) can be written as a product (i.e. series circuit) of three rotation gates or less. Note that for two-level systems such as qubits and spinors, these rotations have a period of 4π. A rotation of 2π (360 degrees) returns the same statevector with a different phase. We also have R b ( − θ ) = R b ( θ ) † {\displaystyle R_{b}(-\theta )=R_{b}(\theta )^{\dagger }} and R b ( 0 ) = I {\displaystyle R_{b}(0)=I} for all b ∈ { x , y , z } . {\displaystyle b\in \{x,y,z\}.} The rotation matrices are related to the Pauli matrices in the following way: R x ( π ) = − i X


id: list-of-quantum-logic-gates-20260505-2
file: data/en.wikipedia.org/wiki/List_of_quantum_logic_gates-2.md
category: reference
title: List of quantum logic gates
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_quantum_logic_gates
date_saved: 2026-05-05T11:07:38.104837+00:00
instance: kb-cron
parent: list-of-quantum-logic-gates-20260505-0
summary:
The √SWAP gate performs half-way of a two-qubit swap (see Clifford gates). It is universal such that any many-qubit gate can be constructed from only √SWAP and single qubit gates. More than one application of the √SWAP is required to produce a Bell state from product states. The √SWAP gate arises naturally in systems that exploit exchange interaction. For systems with Ising like interactions, it is sometimes more natural to introduce the imaginary swap or iSWAP. Note that i SWAP = R x x ( − π / 2 ) R y y ( − π / 2 ) {\displaystyle i{\mbox{SWAP}}=R_{xx}(-\pi /2)R_{yy}(-\pi /2)} and i SWAP = R x x ( − π / 4 ) R y y ( − π / 4 ) {\displaystyle {\sqrt {i{\mbox{SWAP}}}}=R_{xx}(-\pi /4)R_{yy}(-\pi /4)} , or more generally i SWAP n = R x x ( − π / 2 n ) R y y ( − π / 2 n ) {\displaystyle {\sqrt[{n}]{i{\mbox{SWAP}}}}=R_{xx}(-\pi /2n)R_{yy}(-\pi /2n)} for all real n except 0. SWAPα arises naturally in spintronic quantum computers. The Fredkin gate (also CSWAP or CS gate), named after Edward Fredkin, is a 3-bit gate that performs a controlled swap. It is universal for


id: list-of-quantum-processors-20260505-0
file: data/en.wikipedia.org/wiki/List_of_quantum_processors-0.md
category: reference
title: List of quantum processors
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_quantum_processors
date_saved: 2026-05-05T11:07:39.418674+00:00
instance: kb-cron
parent: list-of-quantum-processors-20260505-0
summary:
This list contains quantum processors, also known as quantum processing units (QPUs). Some devices listed below have only been announced at press conferences so far, with no actual demonstrations or scientific publications characterizing the performance. Quantum processors are difficult to compare due to the different architectures and approaches. Due to this, published physical qubit numbers do not reflect the performance levels of the processor. This is instead achieved through the number of logical qubits or benchmarking metrics such as quantum volume, randomized benchmarking or circuit layer operations per second (CLOPS). == Circuit-based quantum processors == These QPUs are based on the quantum circuit and quantum logic gate-based model of computing. == Annealing quantum processors == These QPUs are based on quantum annealing, not to be confused with digital annealing. == Analog quantum processors == These QPUs are based on analog Hamiltonian simulation. == See also == Quantum programming Timeline of quantum computing and communication == References ==


id: magic-quantum-information-20260505-0
file: data/en.wikipedia.org/wiki/Magic_(quantum_information)-0.md
category: reference
title: Magic (quantum information)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Magic_(quantum_information)
date_saved: 2026-05-05T11:07:40.614743+00:00
instance: kb-cron
parent: magic-quantum-information-20260505-0
summary:
In quantum information theory, magic is a property that quantifies the computational resources needed to describe quantum states beyond stabilizer states, which can be efficiently simulated on classical computers. The concept emerged from the Gottesman-Knill theorem proven in the 1990s, which showed that highly entangled stabilizer states offer no quantum computational advantage because they can be simulated just as efficiently on classical computers. In 2014, it was found that magic states are connected to contextuality: in quantum mechanics, it shows that measurement outcomes depend on what other properties are simultaneously measured. Magic is commonly measured using the stabilizer Rényi entropy, which can be experimentally determined through randomized measurement protocols on quantum processors. Without magic, quantum computers cannot perform any computation that classical computers cannot already do, making it essential for achieving quantum computational advantage. In 2024–2025, quantum magic was detected in top quark pairs produced at the Large Hadron Collider; it is the first observation of this property in fundamental particle collisions. The CMS and ATLAS experiments measured correlations between entangled top and anti-top quarks, with the amount of magic depending on the quarks' velocity and direction of travel. Recent theoretical work has revealed a computational phase separation between entanglement-dominated


id: magic-state-distillation-20260505-0
file: data/en.wikipedia.org/wiki/Magic_state_distillation-0.md
category: reference
title: Magic state distillation
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Magic_state_distillation
date_saved: 2026-05-05T11:07:41.772312+00:00
instance: kb-cron
parent: magic-state-distillation-20260505-0
summary:
Magic state distillation is a method for creating more accurate quantum states from multiple noisy ones, which is important for building fault tolerant quantum computers. It has also been linked to quantum contextuality, a concept thought to contribute to quantum computers' power. The technique was first proposed by Emanuel Knill in 2004, and further analyzed by Sergey Bravyi and Alexei Kitaev the same year. Thanks to the Gottesman–Knill theorem, it is known that some quantum operations (operations in the Clifford group) can be perfectly simulated in polynomial time on a classical computer. In order to achieve universal quantum computation, a quantum computer must be able to perform operations outside this set. Magic state distillation achieves this, in principle, by concentrating the usefulness of imperfect resources, represented by mixed states, into states that are conducive for performing operations that are difficult to simulate classically. A variety of qubit magic state distillation routines and distillation routines for qubits with various advantages have been proposed. == Stabilizer formalism == The Clifford group consists of a set of n {\displaystyle n} -qubit operations generated by the gates {H, S, CNOT} (where H is Hadamard and S is [ 1 0 0 i ] {\displaystyle


id: majorana-1-20260505-0
file: data/en.wikipedia.org/wiki/Majorana_1-0.md
category: reference
title: Majorana 1
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Majorana_1
date_saved: 2026-05-05T11:07:42.995461+00:00
instance: kb-cron
parent: majorana-1-20260505-0
summary:
Majorana 1 is a quantum computing processor developed by Microsoft. It uses topological superconductors in an attempt to enable topological quantum computing, which is designed to offer enhanced error robustness compared with conventional quantum computing hardware. It is the first device produced by Microsoft intended for use in quantum computing. It is an indium arsenide-aluminium hybrid device that admits superconductivity at low temperatures. Microsoft claims that it shows some signals of hosting boundary Majorana zero modes. The device can fit eight qubits. Majorana zero modes, if confirmed, could have potential application to making topological qubits, and eventually large-scale topological quantum computers. In its February 2025 announcement, Microsoft claimed that the Majorana 1 represents progress in its long-running project to create a quantum computer based on topological qubits. The announcement has generated both excitement and skepticism within the scientific community, in the absence of definitive public evidence that the Majorana 1 device exhibits Majorana zero modes. == Background == Quantum computing research has historically faced challenges in achieving qubit stability and scalability. Traditional qubits, such as those based on superconducting circuits or trapped ions, are highly susceptible to noise and decoherence, which can introduce errors in computations. To overcome these limitations,


id: microsoft-azure-quantum-20260505-0
file: data/en.wikipedia.org/wiki/Microsoft_Azure_Quantum-0.md
category: reference
title: Microsoft Azure Quantum
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Microsoft_Azure_Quantum
date_saved: 2026-05-05T11:07:44.183216+00:00
instance: kb-cron
parent: microsoft-azure-quantum-20260505-0
summary:
Microsoft Azure Quantum is a public cloud-based quantum computing platform developed by Microsoft, that offers quantum hardware, software, and solutions for developers to build quantum applications. It supports variety of quantum hardware architectures from partners including Quantinuum, IonQ, and Atom Computing. To run applications on the cloud platform, Microsoft developed the Q# quantum programming language. Azure Quantum also includes a platform for scientific research, Azure Quantum Elements. It uses artificial intelligence, high-performance computing and quantum processors to run molecular simulations and calculations in computational chemistry and materials science. Azure Quantum was first announced at Microsoft Ignite in 2019. The platform was opened for public preview in 2021, and Azure Quantum Elements was launched in 2023. == Hardware == In addition to its hardware partners on the platform, Microsoft is developing a topological quantum computer with qubits that are inherently resistant to error. The approach is based on Majorana quasiparticles, which act as their own antiparticle and have a charge and energy equal to zero, making qubits that are more resilient to disturbances. In September 2023, Azure Quantum researchers found evidence consistent with the creation and control of Majorana quasiparticles for topological quantum computing. In November 2024, the qubit virtualization system


id: m-lmer-s-rensen-gate-20260505-0
file: data/en.wikipedia.org/wiki/Mølmer–Sørensen_gate-0.md
category: reference
title: Mølmer–Sørensen gate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mølmer–Sørensen_gate
date_saved: 2026-05-05T11:07:45.564101+00:00
instance: kb-cron
parent: m-lmer-s-rensen-gate-20260505-0
summary:
In quantum computing, Mølmer–Sørensen gate scheme (or MS gate) refers to an implementation procedure for various multi-qubit quantum logic gates used mostly in trapped ion quantum computing. This procedure is based on the original proposition by Klaus Mølmer and Anders Sørensen in 1999–2000. This proposal was an alternative to the 1995 Cirac–Zoller controlled-NOT gate implementation for trapped ions, which requires that the system be restricted to the joint motional ground state of the ions. In an MS gate, entangled states are prepared by illuminating ions with a bichromatic light field. Mølmer and Sørensen identified two regimes in which this is possible: A weak-field regime, where single-photon absorption is suppressed and two-photon processes interfere in a way that makes internal state dynamics insensitive to the vibrational state A strong-field regime where the individual ions are coherently excited, and the motional state is highly entangled with the internal state until all undesirable excitations are deterministically removed toward the end of the interaction. In both regimes, a red and blue sideband interaction are applied simultaneously to each ion, with the red and blue tones symmetrically detuned by δ ′ {\displaystyle \delta '} from the sidebands. This results in laser detunings ± ( ω


id: m-lmer-s-rensen-gate-20260505-1
file: data/en.wikipedia.org/wiki/Mølmer–Sørensen_gate-1.md
category: reference
title: Mølmer–Sørensen gate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mølmer–Sørensen_gate
date_saved: 2026-05-05T11:07:45.564101+00:00
instance: kb-cron
parent: m-lmer-s-rensen-gate-20260505-0
summary:
The above is equivalent to the Ising coupling gate Ryy(π/2); It can then be shown that this gate (along with arbitrary single-qubit rotation) produces a universal set of gates. An alternative definition of MS gate equates it to Rxx(π/2), and is adopted as IonQ's native gate for two-qubit entanglement. In this definition, CNOT gate can be decomposed as CNOT = e − i π 4 ( I − Z 1 ) ( I − X 2 ) = R y 1 ( − π / 2 ) e − i π 4 ( I − X 1 ) ( I − X 2 ) R y 1 ( π / 2 ) = R y 1 ( − π / 2 ) e − i π 4 e i π 4 ( X 1 + X 2 − X 1 ⊗ X 2 ) R y 1 ( π / 2 ) = e − i π 4 R y 1 ( − π / 2 ) R x 1 ( − π / 2 ) R x 2 ( − π / 2 ) R x x ( π / 2 ) R y 1 ( π / 2


id: m-lmer-s-rensen-gate-20260505-2
file: data/en.wikipedia.org/wiki/Mølmer–Sørensen_gate-2.md
category: reference
title: Mølmer–Sørensen gate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mølmer–Sørensen_gate
date_saved: 2026-05-05T11:07:45.564101+00:00
instance: kb-cron
parent: m-lmer-s-rensen-gate-20260505-0
summary:
By making a second rotating wave approximation to neglect oscillation terms, each piece can be examined independently. For δ = 0 {\displaystyle \delta =0} , only the first term is kept, and the Hamiltonian becomes H c a r r i e r = Ω 2 ( σ − + σ + ) , {\displaystyle H_{\rm {carrier}}={\frac {\Omega }{2}}(\sigma _{-}+\sigma _{+}),} which alters the spin state of the ion without affecting its motional state. For δ = − ω 0 {\displaystyle \delta =-\omega _{0}} , only the second term is kept since | δ + ω 0 | ≪ | δ | , | δ − ω 0 | {\displaystyle |\delta +\omega _{0}|\ll |\delta |,|\delta -\omega _{0}|} . Then the red sideband (RSB) Hamiltonian is H R S B = − i η Ω 2 ( a † σ − ) e i ( δ + ω 0 ) t + h . c . {\displaystyle H_{\rm {RSB}}=-i\eta {\frac {\Omega }{2}}(a^{\dagger }\sigma _{-})e^{i(\delta +\omega _{0})t}+h.c.} The RSB transition can be thought of as an `exchange' of motion for spin. For an ion with phonon occupation number n {\displaystyle n} , an RSB π {\displaystyle \pi } -pulse will take |


id: m-lmer-s-rensen-gate-20260505-3
file: data/en.wikipedia.org/wiki/Mølmer–Sørensen_gate-3.md
category: reference
title: Mølmer–Sørensen gate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mølmer–Sørensen_gate
date_saved: 2026-05-05T11:07:45.564101+00:00
instance: kb-cron
parent: m-lmer-s-rensen-gate-20260505-0
summary:
H i n t = i ∑ j , k η j , k Ω j 2 [ e i ( μ k t + ϕ B ) σ − , j a k − e − ( μ k t + ϕ B ) σ + , j a k † + e − i ( μ k t + ϕ R ) σ − , j a k † − e i ( μ k t − ϕ R ) σ + , j a k ] = i ∑ j , k η j , k Ω j 2 [ ( σ − , j e i ϕ s − σ + , j e − i ϕ s ) ( a k e i μ k t e i ϕ m + a k † e − i μ k t e − i ϕ m ) ] ≡ i ∑ j , k η j , k Ω j 2 [ σ ^ j ⊗ A ^ k ( t ) ] {\displaystyle {\begin{aligned}H_{\rm {int}}&=i\sum _{j,k}\eta _{j,k}{\frac {\Omega _{j}}{2}}[e^{i(\mu _{k}t+\phi _{B})}\sigma _{-,j}a_{k}-e^{-(\mu _{k}t+\phi _{B})}\sigma _{+,j}a_{k}^{\dagger }+e^{-i(\mu _{k}t+\phi _{R})}\sigma _{-,j}a_{k}^{\dagger }-e^{i(\mu _{k}t-\phi _{R})}\sigma _{+,j}a_{k}]\\&=i\sum _{j,k}\eta _{j,k}{\frac


id: m-lmer-s-rensen-gate-20260505-4
file: data/en.wikipedia.org/wiki/Mølmer–Sørensen_gate-4.md
category: reference
title: Mølmer–Sørensen gate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mølmer–Sørensen_gate
date_saved: 2026-05-05T11:07:45.564101+00:00
instance: kb-cron
parent: m-lmer-s-rensen-gate-20260505-0
summary:
Vibrational degrees of freedom will enter the scheme only virtually. They are crucial as intermediate states, but population is never transferred to states with different vibrational excitations. This is because the detuning δ ′ {\displaystyle \delta '} is far enough from the mode frequency ω k {\displaystyle \omega _{k}} that negligible population is transferred to intermediate levels with vibration numbers n ± 1 {\displaystyle n\pm 1} . Transition paths involving different, unpopulated vibrational states interfere destructively to eliminate the dependence of rates and revolution frequencies on phonon numbers. This is discussed below. ==== Perturbative analysis ==== If we consider two ions, each illuminated by lasers with detunings δ = ± ( ω k + δ ′ ) {\displaystyle \delta =\pm (\omega _{k}+\delta ')} from ω e g {\displaystyle \omega _{eg}} , the only energy-conserving transitions are | g g ⟩ ↔ | e e ⟩ {\displaystyle |gg\rangle \leftrightarrow |ee\rangle } and | g e ⟩ ↔ | e g ⟩ {\displaystyle |ge\rangle \leftrightarrow |eg\rangle } . Under the Lamb-Dicke approximation e − i η ( a † + a ) ≈ 1 − i η ( a † + a ) {\displaystyle e^{-i\eta (a^{\dagger }+a)}\approx 1-i\eta (a^{\dagger }+a)} , we


id: andrea-morello-20260505-0
file: data/en.wikipedia.org/wiki/Andrea_Morello-0.md
category: reference
title: Andrea Morello
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Andrea_Morello
date_saved: 2026-05-05T11:07:46.747981+00:00
instance: kb-cron
parent: andrea-morello-20260505-0
summary:
Andrea Morello (born 26 June 1972, in Pinerolo, Italy) is the Scientia Professor of Quantum Engineering in the School of Electrical Engineering and Telecommunications at the University of New South Wales, and a Program Manager at the ARC Centre of Excellence for Quantum Computation and Communication Technology (CQC2T). Morello is the head of the Fundamental Quantum Technologies Laboratory at UNSW. == Education == Morello completed his undergraduate degree in electrical engineering at the Politecnico di Torino in Italy in 1998. His research career began at the Grenoble High Magnetic Field Laboratory where he investigated the magnetic phase diagram of high T c {\displaystyle T_{c}} superconductors. He obtained his PhD in experimental physics from the Kamerlingh Onnes Laboratory in Leiden in 2004, during which he explored the quantum dynamics of molecular nanomagnets at low temperatures. Morello spent two years at the University of British Columbia before joining UNSW Sydney in 2006. == Research == Morello's research is primarily focused on designing and building the basic components of a quantum computer using the spins of single atoms in silicon. His team were the first in the world to demonstrate the coherent control and readout of the electron and nuclear spin of an


id: multiverse-computing-20260505-0
file: data/en.wikipedia.org/wiki/Multiverse_Computing-0.md
category: reference
title: Multiverse Computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Multiverse_Computing
date_saved: 2026-05-05T11:07:47.973282+00:00
instance: kb-cron
parent: multiverse-computing-20260505-0
summary:
Multiverse Computing is a quantum AI software company headquartered in San Sebastián, Spain, with offices in Madrid, Barcelona, Zaragoza, Paris, Munich, London, Milan, Toronto and San Francisco. The company develops compressed AI models and quantum software. The AI model compression platform, CompactifAI, delivers compressed AI models by applying tensor network techniques. With its AI model compression technology, the company offers compressed and optimized versions of leading AI models from providers such as OpenAI, Meta, Microsoft, Qwen, DeepSeek or Mistral. It also offers proprietary open-source AI models such as HyperNova 60B available on HuggingFace. == History == Multiverse was co-founded in 2019 by Enrique Lizaso, Román Orús, Alfonso Rubio-Manzanares and Sam Mugel. Lizaso, treasurer and member of the governing board of the European Quantum Industry Consortium, and Orús, Ikerbasque Research Professor at Donostia International Physics Center and former Marie Curie Fellow at the Max Planck Institute of Quantum Optics, were chatting on WhatsApp when the idea for a quantum computing company for finance was born. In 2021, the company announced €12.5 million in funding from the European_Innovation_Council (EIC) Accelerator program. This was followed by a €25 million funding round in 2024, valuing the startup at €100 million. Later that year, the


id: multiverse-computing-20260505-1
file: data/en.wikipedia.org/wiki/Multiverse_Computing-1.md
category: reference
title: Multiverse Computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Multiverse_Computing
date_saved: 2026-05-05T11:07:47.973282+00:00
instance: kb-cron
parent: multiverse-computing-20260505-0
summary:
== Technology == Multiverse Computing’s algorithms have been implemented across verticals such as energy, manufacturing, logistics, finance, chemistry, space, and cybersecurity. In addition to quantum machine learning and optimization algorithms, the company uses quantum-inspired tensor networks to improve efficiency in solving industrial challenges. Tensor networks are used to model quantum systems, specifically quantum systems of many particles, and more recently are being applied to model artificial intelligence systems. In 2023, the company launched CompactifAI, software that utilizes these networks to reduce the computational costs and energy requirements of training and operating large language models (LLMs). By minimizing size, memory, and storage needs of the models, the tensor networks can enhance efficiency and portability of these models. In 2024, the company secured a $1.4M contract with the German Aerospace Center to develop single photon detectors with applications ranging from quantum computing to deep-space communication and bio-imaging. In 2025, Multiverse Computing launched compressed Llama 3.1 8B and Llama 3.3 70B AI models. Both models have 60% fewer parameters than the original models, 84% greater energy efficiency, 40% faster inference, and yield a 50% cost reduction without sacrificing accuracy. AI developers can plug the models into any application – edge, on-premise, or cloud.


id: national-quantum-computing-centre-20260505-0
file: data/en.wikipedia.org/wiki/National_Quantum_Computing_Centre-0.md
category: reference
title: National Quantum Computing Centre
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/National_Quantum_Computing_Centre
date_saved: 2026-05-05T11:07:49.239056+00:00
instance: kb-cron
parent: national-quantum-computing-centre-20260505-0
summary:
The National Quantum Computing Centre (NQCC) is the United Kingdom's national laboratory for quantum computing, located within the Rutherford Appleton Laboratory, in south Oxfordshire. It is part of UK Research and Innovation (UKRI). Construction began in September 2021 and it was officially opened in 2024-10-25. == References ==


id: national-quantum-initiative-act-20260505-0
file: data/en.wikipedia.org/wiki/National_Quantum_Initiative_Act-0.md
category: reference
title: National Quantum Initiative Act
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/National_Quantum_Initiative_Act
date_saved: 2026-05-05T11:07:50.426425+00:00
instance: kb-cron
parent: national-quantum-initiative-act-20260505-0
summary:
The National Quantum Initiative Act is an Act of Congress passed on December 13, 2018, and signed into law on December 21, 2018. The law gives the United States a plan for advancing quantum technology, particularly quantum computing. == Act == The act was passed unanimously by the United States Senate and was signed into law by President Donald Trump. The National Quantum Initiative (NQI) provides an umbrella under which a number of government agencies develop and operate programs related to improving the climate for quantum science and technology in the US, coordinated by the National Quantum Coordination Office. These agencies include the National Institute of Standards and Technology (NIST), the National Science Foundation (NSF), and the United States Department of Energy (DOE). Under the authority of the NQI, the NSF and the DOE have established new research centers and institutes, and NIST has established the Quantum Economic Development Consortium (QED-C), a consortium of industrial, academic, and governmental entities. == Recent Developments == In May 2025, U.S. lawmakers introduced the bipartisan Quantum Sandbox for Near-Term Applications Act (S.1344), aiming to amend the National Quantum Initiative Act. The proposed legislation seeks to establish a public-private partnership to accelerate the development of


id: national-quantum-mission-india-20260505-0
file: data/en.wikipedia.org/wiki/National_Quantum_Mission_India-0.md
category: reference
title: National Quantum Mission India
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/National_Quantum_Mission_India
date_saved: 2026-05-05T11:07:51.644825+00:00
instance: kb-cron
parent: national-quantum-mission-india-20260505-0
summary:
National Quantum Mission India is an initiative by the Department of Science and Technology, Government of India, to foster quantum technologies related scientific and industrial research and development to support national Digital India, Make India, Skill India and Sustainable development goals. == Background == The union cabinet of Government of India approved the National Quantum Mission with a cost of INR 6003.65 cr ($730,297,000) from 2023–24 to 2030–31. Quantum key distribution (QKD) satellites are being developed by ISRO as part of the National Quantum Mission to provide secure communication. == Selection of Thematic Hubs (T-Hubs) and Technical Groups (TGs) == In January 2024, the National Quantum Mission issued a Call for Proposals (CFP), inviting academic and research institutions to contribute to the development of quantum technologies in the areas of Quantum Computing, Communication, Sensing & Metrology andMaterials & Devices. The initiative received 384 submissions from across the country. == Four T-Hubs and 14 TGs Announced == On September 30, 2024, the National Quantum Mission announced four T-Hubs. After evaluation 17 proposals were selected. == References ==


id: neutral-atom-quantum-computer-20260505-0
file: data/en.wikipedia.org/wiki/Neutral_atom_quantum_computer-0.md
category: reference
title: Neutral atom quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neutral_atom_quantum_computer
date_saved: 2026-05-05T11:07:52.888479+00:00
instance: kb-cron
parent: neutral-atom-quantum-computer-20260505-0
summary:
A neutral atom quantum computer is a type of quantum computers built out of Rydberg atoms; this type has many commonalities with trapped-ion quantum computers. As of December 2023, the concept has been used to demonstrate a 48 logical qubit processor. To perform computation, the atoms are first trapped in a magneto-optical trap. Qubits are then encoded in the energy levels of the atoms. Initialization and operation of the computer is performed via the application of lasers on the qubits. For example, the laser can accomplish arbitrary single qubit gates and a C Z {\displaystyle CZ} gate for universal quantum computation. The C Z {\displaystyle CZ} gate is carried out by leveraging the Rydberg blockade which leads to strong interactions when the qubits are physically close to each other. To perform a C Z {\displaystyle CZ} gate, a Rydberg π {\displaystyle \pi } pulse is applied to the control qubit, a 2 π {\displaystyle 2\pi } on the target qubit and then a π {\displaystyle \pi } on the control. Measurement is enforced at the end of the computation with a camera that generates an image of the outcome by measuring the fluorescence of the atoms. == Architecture == Neutral


id: neutral-atom-quantum-computer-20260505-1
file: data/en.wikipedia.org/wiki/Neutral_atom_quantum_computer-1.md
category: reference
title: Neutral atom quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neutral_atom_quantum_computer
date_saved: 2026-05-05T11:07:52.888479+00:00
instance: kb-cron
parent: neutral-atom-quantum-computer-20260505-0
summary:
where, H i = 1 2 ( ( Ω | 1 ⟩ i ⟨ r | + Ω ∗ | r ⟩ i ⟨ 1 | ) − Δ | r ⟩ i ⟨ r | {\displaystyle H_{i}={\frac {1}{2}}((\Omega |1\rangle _{i}\langle r|+\Omega ^{*}|r\rangle _{i}\langle 1|)-\Delta |r\rangle _{i}\langle r|} is the Hamiltonian of i-th atom, Ω {\displaystyle \Omega } is the Rabi frequency of coupling between the Rydberg states and the | 1 ⟩ {\displaystyle |1\rangle } state and Δ {\displaystyle \Delta } is the detuning (see figure to the right for level diagram). When | V r r | >> | Ω | , | Δ | {\displaystyle |V_{rr}|>>|\Omega |,|\Delta |} , we are in the so-called Rydberg Blockade regime. In this regime, the | r r ⟩ {\displaystyle |rr\rangle } state is highly detuned from the rest of the system and thus is effectively decoupled. For the rest of this article, we consider only the Rydberg Blockade regime. The physics of this Hamiltonian can be divided into several subspaces depending on the initial state. The | 00 ⟩ {\displaystyle |00\rangle } state is decoupled and does not evolve. Suppose only the i-th the atom is in | 1 ⟩


id: neutral-atom-quantum-computer-20260505-2
file: data/en.wikipedia.org/wiki/Neutral_atom_quantum_computer-2.md
category: reference
title: Neutral atom quantum computer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neutral_atom_quantum_computer
date_saved: 2026-05-05T11:07:52.888479+00:00
instance: kb-cron
parent: neutral-atom-quantum-computer-20260505-0
summary:
==== Adiabatic gate ==== The adiabatic gate was introduced as an alternative to the Jaksch gate. It is global and symmetric and thus it does not require locally focused lasers. Moreover, the Adiabatic Gate prevents the problem of spurious phase accumulation when the atom is in Rydberg state. In the Adiabatic Gate, instead of doing fast pulses, we dress the atom with an adiabatic pulse sequence that takes the atom on a trajectory around the Bloch sphere and back. The levels pick up a phase on this trip due to the so-called "light shift" induced by the lasers. The shapes of pulses can be chosen to control this phase. If both atoms are in the | 00 ⟩ {\displaystyle |00\rangle } state, nothing happens so | 00 ⟩ → | 00 ⟩ {\displaystyle |00\rangle \rightarrow |00\rangle } . If one of them is in the | 0 ⟩ {\displaystyle |0\rangle } state, the other atom picks up a phase due to light shift: | 01 ⟩ → e i ϕ 1 | 01 ⟩ {\displaystyle |01\rangle \rightarrow e^{i\phi _{1}}|01\rangle } and similarly | 10 ⟩ → e i ϕ 1 | 10 ⟩ {\displaystyle |10\rangle \rightarrow e^{i\phi _{1}}|10\rangle } with:


id: nitrogen-vacancy-center-20260505-0
file: data/en.wikipedia.org/wiki/Nitrogen-vacancy_center-0.md
category: reference
title: Nitrogen-vacancy center
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Nitrogen-vacancy_center
date_saved: 2026-05-05T11:07:54.043665+00:00
instance: kb-cron
parent: nitrogen-vacancy-center-20260505-0
summary:
The nitrogen-vacancy center (N-V center or NV center) is one of numerous photoluminescent point defects in diamond. It consists of a nearest-neighbor pair of a nitrogen atom, which substitutes for a carbon atom, and a lattice vacancy. The most explored and useful properties of an NV center include its spin-dependent photoluminescence (which enables measurement of the electronic spin state using optically detected magnetic resonance), and its relatively long spin coherence at room temperature, lasting up to milliseconds. The NV center energy levels are modified by magnetic fields, electric fields, temperature, and strain, which allow it to serve as a sensor of a variety of physical phenomena. Its atomic size and spin properties can form the basis for useful quantum sensors. NV centers enable nanoscale measurements of magnetic and electric fields, temperature, and mechanical strain with improved precision. External perturbation sensitivity makes NV centers ideal for applications in biomedicine—such as single-molecule imaging and cellular process modeling. NV centers can also be initialized as qubits and enable the implementation of quantum algorithms and networks. It has also been explored for applications in quantum computing (e.g. for entanglement generation), quantum simulation, and spintronics. == Production == Natural NV centers are randomly oriented within


id: nitrogen-vacancy-center-20260505-1
file: data/en.wikipedia.org/wiki/Nitrogen-vacancy_center-1.md
category: reference
title: Nitrogen-vacancy center
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Nitrogen-vacancy_center
date_saved: 2026-05-05T11:07:54.043665+00:00
instance: kb-cron
parent: nitrogen-vacancy-center-20260505-0
summary:
Amplitude and orientation of a static magnetic field splits the ms = ±1 levels in the ground and excited states. Amplitude and orientation of elastic (strain) or electric fields have a much smaller but also more complex effects on the different levels. Continuous-wave microwave radiation (applied in resonance with the transition between ms = 0 and (one of the) ms = ±1 states) changes the population of the sublevels within the ground and excited state. A tunable laser can selectively excite certain sublevels of the ground and excited states. Surrounding spins and spin–orbit interaction will modulate the magnetic field experienced by the NV center. Temperature and pressure affect different parts of the spectrum including the shift between ground and excited states. == Electromagnetic coupling == The Hamiltonian dynamics of a NV center are approximated extremely well by the following sum of interactions with the electromagnetic field: Each term in the Hamiltonian can be measured under the right conditions. === Optical properties === NV centers emit bright red light (3E→3A transitions), if excited off-resonantly by visible green light (3A →3E transitions). This can be done with convenient light sources such as argon or krypton lasers, frequency doubled Nd:YAG lasers, dye lasers,


id: nitrogen-vacancy-center-20260505-2
file: data/en.wikipedia.org/wiki/Nitrogen-vacancy_center-2.md
category: reference
title: Nitrogen-vacancy center
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Nitrogen-vacancy_center
date_saved: 2026-05-05T11:07:54.043665+00:00
instance: kb-cron
parent: nitrogen-vacancy-center-20260505-0
summary:
=== Net charge === It is also possible to switch the charge state of the NV center (i.e. between NV−, NV+ and NV0) by applying a gate voltage. The gate voltage electrically shifts the Fermi level at the diamond surface and changes its surface band bending. Upon varying the gate voltage, individual centers are allowed to switch from an unknown non-fluorescent state to the neutral charge state NV0. The ensemble of centers can be transitioned from NV0 to the qubit state NV−. The diamond surface termination additionally influences the charge state of near-surface NV centers. Oxygen termination is known to stabilize the NV−state by reducing surface conductivity and mitigating band bending. This improves charge state stability and coherence. In a similar capacity, nitrogen termination also affects surface properties and can optimize NV centers for specific sensing applications. Optical excitation methods additionally play a role in charge state manipulation. Illumination with specific wavelengths can induce transitions between charge states. Near-infrared light at 1064 nm has been shown to convert NV0 to NV−, enhancing photoluminescence. Additionally, it has been demonstrated that NV+ centers can be switched to NV0 by photons with energies ≥ {\displaystyle \geq } 1.23 eV. == Applications == The


id: nitrogen-vacancy-center-20260505-3
file: data/en.wikipedia.org/wiki/Nitrogen-vacancy_center-3.md
category: reference
title: Nitrogen-vacancy center
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Nitrogen-vacancy_center
date_saved: 2026-05-05T11:07:54.043665+00:00
instance: kb-cron
parent: nitrogen-vacancy-center-20260505-0
summary:
== Historical remarks == The microscopic model and most optical properties of ensembles of the NV− centers have been firmly established in the 1970s based on the optical measurements combined with uniaxial stress and on the electron paramagnetic resonance. However, a minor error in EPR results (it was assumed that illumination is required to observe NV− EPR signals) resulted in the incorrect multiplicity assignments in the energy level structure. In 1991 it was shown that EPR can be observed without illumination, which established the energy level scheme shown above. The magnetic splitting in the excited state has been measured only recently. The characterization of single NV− centers has become a very competitive field nowadays, with many dozens of papers published in the most prestigious scientific journals. One of the first results was reported back in 1997. In that paper, it was demonstrated that the fluorescence of single NV− centers can be detected by room-temperature fluorescence microscopy and that the defect shows perfect photostability. Also one of the outstanding properties of the NV center was demonstrated, namely room-temperature optically detected magnetic resonance. Despite extensive efforts, electron paramagnetic resonance signals from NV0 avoided detection for decades until 2008. Optical excitation is required


id: noisy-intermediate-scale-quantum-computing-20260505-0
file: data/en.wikipedia.org/wiki/Noisy_intermediate-scale_quantum_computing-0.md
category: reference
title: Noisy intermediate-scale quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Noisy_intermediate-scale_quantum_computing
date_saved: 2026-05-05T11:07:55.205303+00:00
instance: kb-cron
parent: noisy-intermediate-scale-quantum-computing-20260505-0
summary:
Noisy intermediate-scale quantum (NISQ) computing is characterized by quantum processors containing up to 1,000 qubits which are not advanced enough yet for fault-tolerance or large enough to achieve quantum advantage. These processors, which are sensitive to their environment (noisy) and prone to quantum decoherence, are not yet capable of continuous quantum error correction. This intermediate-scale is defined by the quantum volume, which is based on a moderate number of qubits and gate fidelity. The NISQ era is the current state of quantum computer technology, and the term was coined by John Preskill in 2018. According to Microsoft Azure Quantum's scheme, NISQ computation is considered level 1, the lowest of the quantum computing implementation levels. In October 2023, the 1,000 qubit mark was passed for the first time by Atom Computing's 1,180 qubit quantum processor. However, as of 2024, only two quantum processors have over 1,000 qubits, with sub-1,000 quantum processors still remaining the norm. == Algorithms == NISQ algorithms are quantum algorithms designed for quantum processors in the NISQ era. Common examples are the variational quantum eigensolver (VQE) and quantum approximate optimization algorithm (QAOA), which use NISQ devices but offload some calculations to classical processors. These algorithms have been successful


id: noisy-intermediate-scale-quantum-computing-20260505-1
file: data/en.wikipedia.org/wiki/Noisy_intermediate-scale_quantum_computing-1.md
category: reference
title: Noisy intermediate-scale quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Noisy_intermediate-scale_quantum_computing
date_saved: 2026-05-05T11:07:55.205303+00:00
instance: kb-cron
parent: noisy-intermediate-scale-quantum-computing-20260505-0
summary:
==== Performance benchmarks and quantum advantage ==== Recent theoretical and experimental work has demonstrated QAOA's potential for quantum advantage on specific problem classes. For the Max Cut problem on random graphs, QAOA at depth p=11 has been shown to outperform standard semidefinite programming algorithms. Even more remarkably, QAOA can exploit non-adiabatic quantum effects that classical algorithms cannot access, potentially circumventing fundamental limitations that constrain classical optimization methods. Experimental implementations on quantum hardware have shown promising results for problems with up to 20–30 variables, though current hardware limitations restrict practical applications to relatively small problem sizes. The algorithm's performance improves with circuit depth p, but NISQ constraints limit the achievable depth, creating a fundamental trade-off between solution quality and hardware requirement. == Error mitigation: Making noisy quantum computing practical == Since NISQ devices lack full quantum error correction, error mitigation techniques become essential for extracting meaningful results from noisy quantum computations. These techniques operate through post-processing measured data rather than actively correcting errors during computation, making them suitable for near-term hardware implementations. === Zero-noise extrapolation === Zero-noise extrapolation (ZNE) represents one of the most widely used error mitigation techniques, artificially amplifying circuit noise and extrapolating results to the zero-noise limit. The


id: nqit-20260505-0
file: data/en.wikipedia.org/wiki/NQIT-0.md
category: reference
title: NQIT
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/NQIT
date_saved: 2026-05-05T11:07:56.366460+00:00
instance: kb-cron
parent: nqit-20260505-0
summary:
NQIT (Networked Quantum Information Technologies) is a quantum computing research hub established in 2014 as part of the UK National Quantum Technologies Programme. NQIT is a consortium of 9 UK universities and 30 partners, which received funding of £38m over a 5-year period. By the end of the 5-year programme NQIT aims to produce the Q20:20 engine, a demonstration of a scalable quantum computer demonstrator comprising an optically linked network of 20 cells, each cell being a quantum processor with 20 matter qubits. == Organisation == The UK National Quantum Technologies Programme was initiated by the UK Chancellor of the Exchequer, George Osborne in the Autumn Statement in 2013 in which he pledged a £270 million investment. A £120 million national network of four Quantum Technology Hubs was announced by Greg Clark in 2014. The NQIT Hub is led by a Director, Professor Ian Walmsley, who provides overall leadership and scientific vision, and two co-directors, Professor Dominic O’Brien, who leads the Systems Engineering, and Dr Tim Cook, who leads the Industrial User Engagement activities. NQIT is led by the University of Oxford and academic partners are the University of Bath, the University of Cambridge, the University of Edinburgh, the University


id: one-clean-qubit-20260505-0
file: data/en.wikipedia.org/wiki/One_clean_qubit-0.md
category: reference
title: One clean qubit
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/One_clean_qubit
date_saved: 2026-05-05T11:07:57.586244+00:00
instance: kb-cron
parent: one-clean-qubit-20260505-0
summary:
In quantum information, the one clean qubit model of computation is performed an n {\displaystyle n} qubit system with one pure state and n − 1 {\displaystyle n-1} maximally mixed states. This model was motivated by highly mixed states that are prevalent in nuclear magnetic resonance quantum computers. It's described by the density matrix ρ = | 0 ⟩ ⟨ 0 | ⊗ I 2 n − 1 {\displaystyle \rho =\left|0\right\rangle \langle 0|\otimes {\frac {I}{2^{n-1}}}} , where I {\displaystyle I} is the identity matrix. In computational complexity theory, DQC1; also known as the deterministic quantum computation with one clean qubit is the class of decision problems solvable by a one clean qubit machine in polynomial time, upon measuring the first qubit, with an error probability of at most 1/poly(n) for all instances. == Error bounds and composability == The most standard definition of DQC1 requires that measuring the output qubit correctly accepts or rejects the input, with error at most 1 / q ( n ) {\displaystyle 1/q(n)} for specified some polynomial q, given a gap in acceptance probabilities of [ 0 , 1 / 2 − 1 / q ( n ) ] {\displaystyle [0,1/2-1/q(n)]} for NO instances and


id: openqasm-20260505-0
file: data/en.wikipedia.org/wiki/OpenQASM-0.md
category: reference
title: OpenQASM
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenQASM
date_saved: 2026-05-05T11:07:58.731884+00:00
instance: kb-cron
parent: openqasm-20260505-0
summary:
Open Quantum Assembly Language (OpenQASM; pronounced open kazm) is a programming language designed for describing quantum circuits and algorithms for execution on quantum computers. == Language == It is designed to be an intermediate representation that can be used by higher-level compilers to communicate with quantum hardware, and allows for the description of a wide range of quantum operations, as well as classical feed-forward flow control based on measurement outcomes. The language includes a mechanism for describing explicit timing of instructions, and allows for the attachment of low-level definitions to gates for tasks such as calibration. OpenQASM is not intended for general-purpose classical computation, and hardware implementations of the language may not support the full range of data manipulation described in the specification. Compilers for OpenQASM are expected to support a wide range of classical operations for compile-time constants, but the support for these operations on runtime values may vary between implementations. The language was first described in a paper published in July 2017, and a reference source code implementation was released as part of IBM's Quantum Information Software Kit (Qiskit) for use with their IBM Quantum Experience cloud quantum computing platform. The language has similar qualities to traditional hardware


id: parity-measurement-20260505-0
file: data/en.wikipedia.org/wiki/Parity_measurement-0.md
category: reference
title: Parity measurement
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Parity_measurement
date_saved: 2026-05-05T11:07:59.938826+00:00
instance: kb-cron
parent: parity-measurement-20260505-0
summary:
Parity measurement (also referred to as Operator measurement) is a procedure in quantum information science used for error detection in quantum qubits. A parity measurement checks the equality of two qubits to return a true or false answer, which can be used to determine whether a correction needs to occur. Additional measurements can be made for a system greater than two qubits. Because parity measurement does not measure the state of singular bits but rather gets information about the whole state, it is considered an example of a joint measurement. Joint measurements do not have the consequence of destroying the original state of a qubit as normal quantum measurements do. Mathematically speaking, parity measurements are used to project a state into an eigenstate of an operator and to acquire its eigenvalue. Parity measurement is an essential concept of quantum error correction. From the parity measurement, an appropriate unitary operation can be applied to correct the error without knowing the beginning state of the qubit. == Parity and parity checking == A qubit is a two-level system, and when we measure one qubit, we can have either 1 or 0 as a result. One corresponds to odd parity, and zero corresponds


id: parity-measurement-20260505-1
file: data/en.wikipedia.org/wiki/Parity_measurement-1.md
category: reference
title: Parity measurement
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Parity_measurement
date_saved: 2026-05-05T11:07:59.938826+00:00
instance: kb-cron
parent: parity-measurement-20260505-0
summary:
An easy way to visualize this is in the circuit above. First, the input state | ψ ⟩ {\displaystyle |\psi \rangle } is encoded into 3 bits, and parity checks are performed with subsequent error correction performed based on the results of the ancilla qubits at the bottom. Finally, decoding is performing to put get back to the same basis of the input state. == Parity check matrix == A parity check matrix for a quantum circuit can also be constructed using these principles. For some message x encoded as Gx, where G corresponds to the generator matrix, Hx = 0 where H is the parity matrix containing 0's and 1's for a situation where there is no error. However, if an error occurs at one component, then the pattern in the errors can be used to find which bit is incorrect. == Types of parity measurements == Two types of parity measurement are indirect and direct. Indirect parity measurements coincide with the typical way we think of parity measurement as described above, by measuring an ancilla qubit to determine the parity of the input bits. Direct parity measurements differ from the previous type in that a common mode with


id: phase-kickback-20260505-0
file: data/en.wikipedia.org/wiki/Phase_kickback-0.md
category: reference
title: Phase kickback
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Phase_kickback
date_saved: 2026-05-05T11:08:01.130073+00:00
instance: kb-cron
parent: phase-kickback-20260505-0
summary:
In quantum computing, phase kickback refers to the fact that controlled operations have effects on their controls, in addition to on their targets, and that these effects correspond to phasing operations. When a controlled operation, such as a Controlled NOT (CNOT) gate, is applied to two qubits, the phase of the second (target) qubit is conditioned on the state of the first (control) qubit. Because the phase of the second qubit is being "kicked back" to the first qubit, this phenomenon was coined "phase kickback" in 1997 by Richard Cleve, Artur Ekert, Chiara Macchiavello, and Michele Mosca through a paper that solved the Deutsch-Jozsa problem. For example, when a controlled NOT gate's target qubit is in the state 1 / 2 ( | 0 ⟩ − | 1 ⟩ ) {\displaystyle 1/{\sqrt {2}}(|0\rangle -|1\rangle )} , the effect of the controlled NOT gate is equivalent to the effect of applying a Pauli Z gate to the controlled NOT's control qubit. Phase kickback is one of the key effects that distinguishes quantum computation from classical computation. Phase kickback also provides a justification for why qubits would be disrupted by measurements: a measurement is an operation that flips a classical bit (the


id: phase-kickback-20260505-1
file: data/en.wikipedia.org/wiki/Phase_kickback-1.md
category: reference
title: Phase kickback
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Phase_kickback
date_saved: 2026-05-05T11:08:01.130073+00:00
instance: kb-cron
parent: phase-kickback-20260505-0
summary:
| ψ ⟩ {\displaystyle |\psi \rangle } must be an eigenvector of controlled operator U {\displaystyle U} . When | ψ ⟩ {\displaystyle |\psi \rangle } is an eigenvector of U {\displaystyle U} , U | ψ ⟩ = e i ϕ | ψ ⟩ {\displaystyle U|\psi \rangle =e^{i\phi }|\psi \rangle } . At point B of the above circuit, the system will then have state | 0 ⟩ | ψ ⟩ + | 1 ⟩ e i ϕ | ψ ⟩ 2 = | 0 ⟩ + e i ϕ | 1 ⟩ 2 | ψ ⟩ {\displaystyle {\frac {|0\rangle |\psi \rangle +|1\rangle e^{i\phi }|\psi \rangle }{\sqrt {2}}}={\frac {|0\rangle +e^{i\phi }|1\rangle }{\sqrt {2}}}|\psi \rangle } . Now, e i ϕ {\displaystyle e^{i\phi }} will be associated with the first qubit when this state is factored out into individual states (assuming the system is not entangled). From this, it can be seen that when | ψ ⟩ {\displaystyle |\psi \rangle } is an eigenvector of U {\displaystyle U} , the control qubit is able to change by being multiplied by the phase while the target qubit remains unchanged. Operator U {\displaystyle U} must be used in a controlled way. In


id: physical-and-logical-qubits-20260505-0
file: data/en.wikipedia.org/wiki/Physical_and_logical_qubits-0.md
category: reference
title: Physical and logical qubits
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Physical_and_logical_qubits
date_saved: 2026-05-05T11:08:02.278467+00:00
instance: kb-cron
parent: physical-and-logical-qubits-20260505-0
summary:
In quantum computing, a qubit is a unit of information analogous to a bit (binary digit) in classical computing, but it is affected by quantum mechanical properties such as superposition and entanglement which allow qubits to be in some ways more powerful than classical bits for some tasks. Qubits are used in quantum circuits and quantum algorithms composed of quantum logic gates to solve computational problems, where they are used for input/output and intermediate computations. A physical qubit is a physical device that behaves as a two-state quantum system, used as a component of a computer system. A logical qubit is a physical or abstract qubit that performs as specified in a quantum algorithm or quantum circuit subject to unitary transformations, has a long enough coherence time to be usable by quantum logic gates (cf. propagation delay for classical logic gates). Since the development of the first quantum computer in 1998, most technologies used to implement qubits face issues of stability, decoherence, fault tolerance and scalability. Because of this, many physical qubits are needed for the purposes of error-correction to produce an entity which behaves logically as a single qubit would in a quantum circuit or algorithm; this is the


id: planqc-20260505-0
file: data/en.wikipedia.org/wiki/Planqc-0.md
category: reference
title: Planqc
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Planqc
date_saved: 2026-05-05T11:08:03.451786+00:00
instance: kb-cron
parent: planqc-20260505-0
summary:
planqc is a quantum computing company based in Garching. Founded in 2022 as a spin-off from the Max Planck Institute of Quantum Optics, the company develops quantum processors that use neutral atoms trapped in optical lattices of light to perform computations. == History == planqc was founded in 2022 by Alexander Glätzle, Sebastian Blatt, and Johannes Zeiher as the first spin-off from the Max Planck Institute of Quantum Optics within the Munich Quantum Valley initiative. The company is part of broader European efforts to develop locally built quantum computing technologies. The company’s founders and leadership include researchers formerly affiliated with the University of Oxford, Harvard University, and the University of California, Berkeley. In the same year, planqc secured seed funding of approximately €4.6 million from UVC Partners and Speedinvest to support the development of its neutral-atom quantum processors. Among the investors were Hermann Hauser, Ann-Kristin Achleitner, and Markus Wagner, who also joined the company's advisory board. planqc’s scientific advisory board includes researchers in quantum physics, such as Immanuel Bloch, J. Ignacio Cirac, Artur Ekert, Dieter Jaksch, and Markus Müller. In 2023, the company was selected by the German Aerospace Center (DLR) to develop a 1,000-qubit quantum computer under a contract


id: qmill-20260505-0
file: data/en.wikipedia.org/wiki/QMill-0.md
category: reference
title: QMill
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/QMill
date_saved: 2026-05-05T11:08:04.681605+00:00
instance: kb-cron
parent: qmill-20260505-0
summary:
QMill is a quantum computing firm based in Finland that was established in 2024, focusing on creating quantum algorithms that offer immediate, practical advantages for industrial uses. Utilizing upcoming quantum technology, QMill strives to tackle intricate optimization challenges and deliver considerable value across multiple industries. The organization is situated in Espoo, Finland. == References == == External links == Official website


id: qpiai-indus-20260505-0
file: data/en.wikipedia.org/wiki/QpiAI-Indus-0.md
category: reference
title: QpiAI-Indus
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/QpiAI-Indus
date_saved: 2026-05-05T11:08:05.842605+00:00
instance: kb-cron
parent: qpiai-indus-20260505-0
summary:
QpiAI-Indus is the India's first full stack quantum computer. It is a 25 superconducting qubits quantum computer developed by the Banglore based startup company QpiAI. It was launched on the occasion of the World Quantum Day in the year 2025. The quantum computer QpiAI-Indus was developed under the leadership of the CEO Nagendra Nagaraja of the company. The development program of the quantum computer was assisted and supported by the National Quantum Mission of the Government of India. The success of the development of the QpiAI-Indus quantum computer at the silicon city Bangalore in India is considered as one of major milestone in journey of India's quantum computer. == Etymology == QpiAI-Indus is the codename of the 25 qubits quantum computer developed by the startup company QpiAI. In the term QpiAI which also signifies for the company name, the letter Q stands for quantum, pi stands for the mathematical symbol π and AI means algorithmic intelligence. The term Indus signifies for the ancient civilization valley in the Indian subcontinent. Thus the etymology of the codename of the quantum computer QpiAI-Indus signifies the legacy of the development of quantum computing in India. == Description == The QpiAI-Indus quantum computer features a


id: quantum-algorithm-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_algorithm-0.md
category: reference
title: Quantum algorithm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_algorithm
date_saved: 2026-05-05T11:08:07.005881+00:00
instance: kb-cron
parent: quantum-algorithm-20260505-0
summary:
In quantum computing, a quantum algorithm is an algorithm that runs on a realistic model of quantum computation, the most commonly used model being the quantum circuit model of computation. A classical (or non-quantum) algorithm is a finite sequence of instructions, or a step-by-step procedure for solving a problem, where each step or instruction can be performed on a classical computer. Similarly, a quantum algorithm is a step-by-step procedure, where each of the steps can be performed on a quantum computer. Although all classical algorithms can also be performed on a quantum computer, the term quantum algorithm is generally reserved for algorithms that seem inherently quantum, or use some essential feature of quantum computation such as quantum superposition or quantum entanglement. Problems that are undecidable using classical computers remain undecidable using quantum computers. What makes quantum algorithms interesting is that they might be able to solve some problems faster than classical algorithms because the quantum superposition and quantum entanglement that quantum algorithms exploit generally cannot be efficiently simulated on classical computers (see Quantum supremacy). The best-known algorithms are Shor's algorithm for factoring and Grover's algorithm for searching an unstructured database or an unordered list. Shor's algorithm would, if implemented, run


id: quantum-algorithm-20260505-1
file: data/en.wikipedia.org/wiki/Quantum_algorithm-1.md
category: reference
title: Quantum algorithm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_algorithm
date_saved: 2026-05-05T11:08:07.005881+00:00
instance: kb-cron
parent: quantum-algorithm-20260505-0
summary:
| f ~ ( z i ) | ⩾ 2. {\displaystyle |{\tilde {f}}(z_{i})|\geqslant 2.} This can be done in bounded-error quantum polynomial time (BQP). == Algorithms based on amplitude amplification == Amplitude amplification is a technique that allows the amplification of a chosen subspace of a quantum state. Applications of amplitude amplification usually lead to quadratic speedups over the corresponding classical algorithms. It can be considered as a generalization of Grover's algorithm. === Grover's algorithm === Grover's algorithm searches an unstructured database (or an unordered list) with N entries for a marked entry, using only O ( N ) {\displaystyle O({\sqrt {N}})} queries instead of the O ( N ) {\displaystyle O({N})} queries required classically. Classically, O ( N ) {\displaystyle O({N})} queries are required even allowing bounded-error probabilistic algorithms. Theorists have considered a hypothetical generalization of a standard quantum computer that could access the histories of the hidden variables in Bohmian mechanics. (Such a computer is completely hypothetical and would not be a standard quantum computer, or even possible under the standard theory of quantum mechanics.) Such a hypothetical computer could implement a search of an N-item database in at most O ( N 3 ) {\displaystyle O({\sqrt[{3}]{N}})} steps.


id: quantum-algorithm-20260505-2
file: data/en.wikipedia.org/wiki/Quantum_algorithm-2.md
category: reference
title: Quantum algorithm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_algorithm
date_saved: 2026-05-05T11:08:07.005881+00:00
instance: kb-cron
parent: quantum-algorithm-20260505-0
summary:
=== Formula evaluation === A formula is a tree with a gate at each internal node and an input bit at each leaf node. The problem is to evaluate the formula, which is the output of the root node, given oracle access to the input. A well studied formula is the balanced binary tree with only NAND gates. This type of formula requires Θ ( N c ) {\displaystyle \Theta (N^{c})} queries using randomness, where c = log 2 ⁡ ( 1 + 33 ) / 4 ≈ 0.754 {\displaystyle c=\log _{2}(1+{\sqrt {33}})/4\approx 0.754} . With a quantum algorithm, however, it can be solved in Θ ( N 1 / 2 ) {\displaystyle \Theta (N^{1/2})} queries. No better quantum algorithm for this case was known until one was found for the unconventional Hamiltonian oracle model. The same result for the standard setting soon followed. Fast quantum algorithms for more complicated formulas are also known. === Group commutativity === The problem is to determine if a black-box group, given by k generators, is commutative. A black-box group is a group with an oracle function, which must be used to perform the group operations (multiplication, inversion, and comparison with identity). The interest


id: quantum-artificial-intelligence-lab-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_Artificial_Intelligence_Lab-0.md
category: reference
title: Quantum Artificial Intelligence Lab
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_Artificial_Intelligence_Lab
date_saved: 2026-05-05T11:08:08.332857+00:00
instance: kb-cron
parent: quantum-artificial-intelligence-lab-20260505-0
summary:
The Quantum Artificial Intelligence Lab (also called the Quantum AI Lab or QuAIL) is a joint initiative of NASA, Universities Space Research Association, and Google (specifically, Google Research) whose goal is to pioneer research on how quantum computing might help with machine learning and other difficult computer science problems. The lab is hosted at NASA's Ames Research Center. == History == The Quantum AI Lab was announced by Google Research in a blog post on May 16, 2013. At the time of launch, the Lab was using the most advanced commercially available quantum computer, D-Wave Two from D-Wave Systems. On October 10, 2013, Google released a short film describing the current state of the Quantum AI Lab. On October 18, 2013, Google announced that it had incorporated quantum physics into Minecraft. In January 2014, Google reported results comparing the performance of the D-Wave Two in the lab with that of classical computers. The results were ambiguous and provoked heated discussion on the Internet. On 2 September 2014, it was announced that the Google Quantum AI Lab, in partnership with UC Santa Barbara, would be launching an initiative to create quantum information processors based on superconducting electronics. On the 23rd of


id: quantum-computation-and-quantum-information-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_Computation_and_Quantum_Information-0.md
category: reference
title: Quantum Computation and Quantum Information
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_Computation_and_Quantum_Information
date_saved: 2026-05-05T11:08:09.577704+00:00
instance: kb-cron
parent: quantum-computation-and-quantum-information-20260505-0
summary:
Quantum Computation and Quantum Information is a textbook about quantum information science written by Michael Nielsen and Isaac Chuang, regarded as a standard text on the subject. It is informally known as "Mike and Ike", after the candies of that name. The book assumes minimal prior experience with quantum mechanics and with computer science, aiming instead to be a self-contained introduction to the relevant features of both. (Lov Grover recalls a postdoc disparaging it with the remark, "The book is too elementary – it starts off with the assumption that the reader does not even know quantum mechanics.") The focus of the text is on theory, rather than the experimental implementations of quantum computers, which are discussed more briefly. As of December 2024, the book has been cited over 58,000 times on Google Scholar. In 2019, Nielsen adapted parts of the book for his Quantum Country project. == Table of Contents (Tenth Anniversary Edition) == Chapter 1: Introduction and Overview Chapter 2: Introduction to Quantum Mechanics Chapter 3: Introduction to Computer Science Chapter 4: Quantum Circuits Chapter 5: The Quantum Fourier Transform and its Applications Chapter 6: Quantum Search Algorithms Chapter 7: Quantum Computers: Physical Realization Chapter 8: Quantum Noise


id: quantum-computing-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_computing-0.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
A quantum computer is a real or theoretical computer that exploits quantum phenomena like superposition and entanglement in an essential way. It is widely believed that a quantum computer could perform some calculations exponentially faster than any classical computer. For example, a large-scale quantum computer could break some widely used encryption schemes and aid physicists in performing physical simulations. However, current hardware implementations of quantum computation are largely experimental and only suitable for specialized tasks. The basic unit of information in quantum computing, the qubit (or "quantum bit"), serves the same function as the bit in ordinary or "classical" computing. However, unlike a classical bit, which can be in one of two states (a binary), a qubit can exist in a linear combination of two states known as a quantum superposition. The result of measuring a qubit is one of the two states given by a probabilistic rule. If a quantum computer manipulates the qubit in a particular way, wave interference effects amplify the probability of the desired measurement result. The design of quantum algorithms involves creating procedures that allow a quantum computer to perform this amplification. Quantum computers are not yet practical for real-world applications. Physically engineering high-quality qubits


id: quantum-computing-20260505-1
file: data/en.wikipedia.org/wiki/Quantum_computing-1.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
A classical computer is a quantum computer ... so we shouldn't be asking about "where do quantum speedups come from?" We should say, "Well, all computers are quantum. ... Where do classical slowdowns come from?" === Quantum information === Just as the bit is the basic concept of classical information theory, the qubit is the fundamental unit of quantum information. The same term qubit is used to refer to an abstract mathematical model and to any physical system that is represented by that model. A classical bit, by definition, exists in either of two physical states, which can be denoted 0 and 1. A qubit is also described by a state, and two states, often written | 0 ⟩ {\displaystyle |0\rangle } and | 1 ⟩ {\displaystyle |1\rangle } , serve as the quantum counterparts of the classical states 0 and 1. However, the quantum states | 0 ⟩ {\displaystyle |0\rangle } and | 1 ⟩ {\displaystyle |1\rangle } belong to a vector space, meaning that they can be multiplied by constants and added together, and the result is again a valid quantum state. Such a combination is known as a superposition of | 0 ⟩ {\displaystyle |0\rangle } and


id: quantum-computing-20260505-2
file: data/en.wikipedia.org/wiki/Quantum_computing-2.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
CNOT := ( 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 ) . {\displaystyle \operatorname {CNOT} :={\begin{pmatrix}1&0&0&0\\0&1&0&0\\0&0&0&1\\0&0&1&0\end{pmatrix}}.} As a mathematical consequence of this definition, CNOT ⁡ | 00 ⟩ = | 00 ⟩ {\textstyle \operatorname {CNOT} |00\rangle =|00\rangle } , CNOT ⁡ | 01 ⟩ = | 01 ⟩ {\textstyle \operatorname {CNOT} |01\rangle =|01\rangle } , CNOT ⁡ | 10 ⟩ = | 11 ⟩ {\textstyle \operatorname {CNOT} |10\rangle =|11\rangle } , and CNOT ⁡ | 11 ⟩ = | 10 ⟩ {\textstyle \operatorname {CNOT} |11\rangle =|10\rangle } . In other words, the CNOT applies a NOT gate ( X {\textstyle X} from before) to the second qubit if and only if the first qubit is in the state | 1 ⟩ {\textstyle |1\rangle } . If the first qubit is | 0 ⟩ {\textstyle |0\rangle } , nothing is done to either qubit. In summary, quantum computation can be described as a network of quantum logic gates and measurements. However, any measurement can be deferred to the end of quantum computation, though this deferment may come at a computational cost, so most quantum circuits depict a network consisting only of quantum


id: quantum-computing-20260505-3
file: data/en.wikipedia.org/wiki/Quantum_computing-3.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
Digital cryptography enables communications to remain private, preventing unauthorized parties from accessing them. Conventional encryption, the obscuring of a message with a key through an algorithm, relies on the algorithm being difficult to reverse. Encryption is also the basis for digital signatures and authentication mechanisms. Quantum computing may be sufficiently more powerful that difficult reversals are feasible, allowing messages relying on conventional encryption to be read. Quantum cryptography replaces conventional algorithms with computations based on quantum computing. In principle, quantum encryption would be impossible to decode even with a quantum computer. This advantage comes at a significant cost in terms of elaborate infrastructure, while effectively preventing legitimate decoding of messages by governmental security officials. Ongoing research in quantum and post-quantum cryptography has led to new algorithms for quantum key distribution, initial work on quantum random number generation and to some early technology demonstrations. == Communication == Quantum cryptography enables new ways to transmit data securely; for example, quantum key distribution uses entangled quantum states to establish secure cryptographic keys. When a sender and receiver exchange quantum states, they can guarantee that an adversary does not intercept the message, as any unauthorized eavesdropper would disturb the delicate quantum system and introduce


id: quantum-computing-20260505-4
file: data/en.wikipedia.org/wiki/Quantum_computing-4.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
A notable application of quantum computing is in attacking cryptographic systems that are currently in use. Integer factorization, which underpins the security of public key cryptographic systems, is believed to be computationally infeasible on a classical computer for large integers if they are the product of a few prime numbers (e.g., the product of two 300-digit primes). By contrast, a quantum computer could solve this problem exponentially faster using Shor's algorithm to factor the integer. This ability would allow a quantum computer to break many of the cryptographic systems in use today, in the sense that there would be a polynomial time (in the number of digits of the integer) algorithm for solving the problem. In particular, most of the popular public key ciphers are based on the difficulty of factoring integers or the discrete logarithm problem, both of which can be solved by Shor's algorithm. In particular, the RSA, Diffie–Hellman, and elliptic curve Diffie–Hellman algorithms could be broken. These are used to protect secure Web pages, encrypted email, and many other types of data. Breaking these would have significant ramifications for electronic privacy and security. Identifying cryptographic systems that may be secure against quantum algorithms is an actively researched


id: quantum-computing-20260505-5
file: data/en.wikipedia.org/wiki/Quantum_computing-5.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
Deep generative chemistry models have been explored for potential applications in drug discovery. Early experimental work has explored the use of near-term quantum hardware in molecular generative modeling for drug discovery. In 2023, researchers at Gero reported a hybrid quantum–classical generative model based on a restricted Boltzmann machine, implemented on a commercially available quantum annealing device, to generate novel drug-like small molecules with physicochemical properties comparable to known medicinal compounds. However, the immense size and complexity of the structural space of all possible drug-like molecules pose significant obstacles, which could be overcome in the future by quantum computers. Quantum computers are naturally good for solving complex quantum many-body problems and thus may be instrumental in applications involving quantum chemistry. Therefore, one can expect that quantum-enhanced generative models including quantum GANs may eventually be developed into ultimate generative chemistry algorithms. == Engineering == As of 2023, classical computers outperform quantum computers for all real-world applications. While current quantum computers may speed up solutions to particular mathematical problems, they give no computational advantage for practical tasks. Scientists and engineers are exploring multiple technologies for quantum computing hardware and hope to develop scalable quantum architectures, but serious obstacles remain. In practice, improvements in


id: quantum-computing-20260505-6
file: data/en.wikipedia.org/wiki/Quantum_computing-6.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
==== Decoherence ==== One of the greatest challenges involved in constructing quantum computers is controlling or removing quantum decoherence. This usually means isolating the system from its environment, as interactions with the external world cause the system to decohere. However, other sources of decoherence also exist. Examples include the quantum gates, the lattice vibrations, and the background thermonuclear spin of the physical system used to implement the qubits. Decoherence is irreversible, as it is effectively non-unitary, and is usually something that should be highly controlled, if not avoided. Decoherence times for candidate systems in particular, the transverse relaxation time T2 (for NMR and MRI technology, also called the dephasing time), typically range between nanoseconds and seconds at low temperatures. Currently, some quantum computers require their qubits to be cooled to 20 millikelvin (usually using a dilution refrigerator) in order to prevent significant decoherence. A 2020 study argues that ionizing radiation such as cosmic rays can nevertheless cause certain systems to decohere within milliseconds. As a result, time-consuming tasks may render some quantum algorithms inoperable, as attempting to maintain the state of qubits for a long enough duration will eventually corrupt the superpositions. These issues are more difficult for optical approaches


id: quantum-computing-20260505-7
file: data/en.wikipedia.org/wiki/Quantum_computing-7.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
=== Skepticism === Despite high hopes for quantum computing, significant progress in hardware, and optimism about future applications, a 2023 Nature spotlight article summarized current quantum computers as being "For now, [good for] absolutely nothing". The article elaborated that quantum computers are yet to be more useful or efficient than conventional computers in any case, though it also argued that, in the long term, such computers are likely to be useful. A 2023 Communications of the ACM article found that current quantum computing algorithms are "insufficient for practical quantum advantage without significant improvements across the software/hardware stack". It argues that the most promising candidates for achieving speedup with quantum computers are "small-data problems", for example, in chemistry and materials science. However, the article also concludes that a large range of the potential applications it considered, such as machine learning, "will not achieve quantum advantage with current quantum algorithms in the foreseeable future", and it identified I/O constraints that make speedup unlikely for "big data problems, unstructured linear systems, and database search based on Grover's algorithm". This state of affairs can be traced to several current and long-term considerations. Conventional computer hardware and algorithms are not only optimized for practical tasks,


id: quantum-computing-20260505-8
file: data/en.wikipedia.org/wiki/Quantum_computing-8.md
category: reference
title: Quantum computing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing
date_saved: 2026-05-05T11:08:10.743299+00:00
instance: kb-cron
parent: quantum-computing-20260505-0
summary:
While quantum computers cannot solve any problems that classical computers cannot already solve, it is suspected that they can solve certain problems faster than classical computers. For instance, it is known that quantum computers can efficiently factor integers, while this is not believed to be the case for classical computers. The class of problems that can be efficiently solved by a quantum computer with bounded error is called BQP, for "bounded error, quantum, polynomial time". More formally, BQP is the class of problems that can be solved by a polynomial-time quantum Turing machine with an error probability of at most 1/3. As a class of probabilistic problems, BQP is the quantum counterpart to BPP ("bounded error, probabilistic, polynomial time"), the class of problems that can be solved by polynomial-time probabilistic Turing machines with bounded error. It is known that B P P ⊆ B Q P {\displaystyle {\mathsf {BPP\subseteq BQP}}} but there is no proof B Q P ≠ B P P {\displaystyle {\mathsf {BQP\neq BPP}}} , which intuitively would mean that quantum computers are more powerful than classical computers in terms of time complexity. The exact relationship of BQP to P, NP, and PSPACE is not known. However, it


id: quantum-volume-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_volume-0.md
category: reference
title: Quantum volume
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_volume
date_saved: 2026-05-05T11:08:11.904022+00:00
instance: kb-cron
parent: quantum-volume-20260505-0
summary:
Quantum volume is a metric that measures the capabilities and error rates of a quantum computer. It expresses the maximum size of square quantum circuits that can be implemented successfully by the computer. The form of the circuits is independent from the quantum computer architecture, but compiler can transform and optimize it to take advantage of the computer's features. Thus, quantum volumes for different architectures can be compared. == Introduction == Quantum computers are difficult to compare. Quantum volume is a single number designed to show all around performance. It is a measurement and not a calculation, and takes into account several features of a quantum computer, starting with its number of qubits—other measures used are gate and measurement errors, crosstalk and connectivity. IBM defined its Quantum Volume metric because a classical computer's transistor count and a quantum computer's quantum bit count aren't the same. Qubits decohere with a resulting loss of performance so a few fault tolerant bits are more valuable as a performance measure than a larger number of noisy, error-prone qubits. Generally, the larger the quantum volume, the more complex the problems a quantum computer can solve. Alternative benchmarks include Cross-entropy benchmarking, reliable Quantum Operations per Second


id: quantum-computing-scaling-laws-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_computing_scaling_laws-0.md
category: reference
title: Quantum computing scaling laws
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_computing_scaling_laws
date_saved: 2026-05-05T11:08:13.112711+00:00
instance: kb-cron
parent: quantum-computing-scaling-laws-20260505-0
summary:
Quantum computing scaling laws (sometimes abbreviated as QC scaling laws) are a set of observations describing the exponential growth of various aspects of quantum computer development. The most important scaling laws in quantum computing are Rose's law, Neven's law, and Schoelkopf's law. These laws are named after prominent quantum computing researchers and predict continued improvement in quantum computer performance in the coming years. However, it is important to note that these laws are more empirical rules of thumb and predictions based on observations rather than immutable truths, and technological development may bring unexpected challenges and breakthroughs. == Rose's law == Rose's law observes that the number of qubits on chips doubles roughly every 18 months. The law is often described as the quantum-computing equivalent of Moore's law. The term was coined by Steve Jurvetson after meeting D-Wave founder Geordie Rose. This law attempts to measure rapid processor scaling, though different quantum computing technologies may follow different trajectories depending on their design constraints. == Neven's law == Neven's law states that the computational power of quantum computers appears to be growing at a doubly exponential rate. In other words, not only is computational power increasing exponentially—that exponential growth is itself accelerating


id: quantum-computing-since-democritus-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_Computing_Since_Democritus-0.md
category: reference
title: Quantum Computing Since Democritus
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_Computing_Since_Democritus
date_saved: 2026-05-05T11:08:14.294374+00:00
instance: kb-cron
parent: quantum-computing-since-democritus-20260505-0
summary:
Quantum Computing Since Democritus is a 2013 book on quantum information science written by Scott Aaronson. It is loosely based on a course Aaronson taught at the University of Waterloo, Canada, the lecture notes for which are available online. == Contents == Aaronson has stated that he intends the book to be at the same level as Leonard Susskind's The Theoretical Minimum or Roger Penrose's The Road to Reality; Physics Today compared it to George Gamow's One Two Three... Infinity. The book covers everything from computer science to mathematics to quantum mechanics and quantum computing, starting, as the title indicates, with Democritus. === Front cover === The front cover image is an oil canvas painting of Democritus by Hendrik ter Brugghen dated 1628. It depicts Democritus as a young, laughing hedonist who points in the distance, as to where the folly of mankind is found. The image invokes Aaronson's discussions on Democritus' concept of atoms and the void, which forms the foundational understanding of matter at the atomic level, is relevant to quantum computing, where manipulating and controlling individual quantum objects for calculations echoes the early atomic theory's significance. == Author == Scott Aaronson is a professor of theoretical computer


id: quantum-computing-a-gentle-introduction-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_Computing:_A_Gentle_Introduction-0.md
category: reference
title: Quantum Computing: A Gentle Introduction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_Computing:_A_Gentle_Introduction
date_saved: 2026-05-05T11:08:15.435261+00:00
instance: kb-cron
parent: quantum-computing-a-gentle-introduction-20260505-0
summary:
Quantum Computing: A Gentle Introduction is a textbook on quantum computing. It was written by Eleanor Rieffel and Wolfgang Polak, and published in 2011 by the MIT Press. == Topics == Although the book approaches quantum computing through the model of quantum circuits, it is focused more on quantum algorithms than on the construction of quantum computers. It has 13 chapters, divided into three parts: "Quantum building blocks" (chapters 1–6), "Quantum algorithms" (chapters 7–9), and "Entangled subsystems and robust quantum computation" (chapters 10–13). After an introductory chapter overviewing related topics including quantum cryptography, quantum information theory, and quantum game theory, chapter 2 introduces quantum mechanics and quantum superposition using polarized light as an example, also discussing qubits, the Bloch sphere representation of the state of a qubit, and quantum key distribution. Chapter 3 introduces direct sums, tensor products, and quantum entanglement, and chapter 4 includes the EPR paradox, Bell's theorem on the impossibility of local hidden variable theories, as quantified by Bell's inequality. Chapter 5 discusses unitary operators, quantum logic gates, quantum circuits, and functional completeness for systems of quantum gates. Chapter 6, the final chapter of the building block section, discusses (classical) reversible computing, and the conversion of arbitrary


id: quantum-error-correction-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_error_correction-0.md
category: reference
title: Quantum error correction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_error_correction
date_saved: 2026-05-05T11:08:16.683136+00:00
instance: kb-cron
parent: quantum-error-correction-20260505-0
summary:
Quantum error correction (QEC) comprises a set of techniques used in quantum memory and quantum computing to protect quantum information from errors arising from decoherence and other sources of quantum noise. QEC schemes that employ codewords stabilized by a set of commuting operators are known as stabilizer codes, and the corresponding codewords are referred to as quantum error-correcting codes (QECCs). Conceptually, to use a quantum error-correcting code, one can append ancilla qubits to qubits that need protection, and apply a unitary encoding circuit to rotate the global state into a subspace of a larger Hilbert space. This highly entangled, encoded state corrects for local noisy errors. A quantum error-correcting code makes quantum computation and quantum communication practical by providing a way for a sender and receiver to simulate a noiseless qubit channel given a noisy qubit channel whose noise conforms to a particular error model. == Overview == Much of the terminology in QEC is derived from its classical counterpart, the classical error-correcting code. In classical coding theory, a code is commonly denoted by the notation [ n , k , d ] {\displaystyle [n,k,d]} , which represents the encoding of k {\displaystyle k} logical bits into n {\displaystyle n}


id: quantum-error-correction-20260505-1
file: data/en.wikipedia.org/wiki/Quantum_error_correction-1.md
category: reference
title: Quantum error correction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_error_correction
date_saved: 2026-05-05T11:08:16.683136+00:00
instance: kb-cron
parent: quantum-error-correction-20260505-0
summary:
=== More general QEC schemes === The [ [ n , k , d ] ] {\displaystyle [[n,k,d]]} QECCs do not encompass all possible quantum codes. These belong to the class of additive codes, defined within the stabilizer formalism. A more general class, known as non-additive codes, extends beyond this framework. For instance, the ( ( 5 , 6 , 2 ) ) {\displaystyle ((5,6,2))} code encodes more than two qubits ( log 2 ⁡ 6 ≈ 2.585 ) {\displaystyle (\log _{2}6\approx 2.585)} into five physical qubits with code distance two. Non-additive codes can, in principle, achieve higher code rates than additive ones, but their construction and analysis are considerably more challenging. As a result, they remain relatively unexplored, with only limited studies to date. Beyond encoding qubits into qubits, quantum information can also be stored in more general physical systems, such as d {\displaystyle d} -level systems (qudits) or infinite-dimensional oscillators. Encoding a smaller logical system into a larger physical Hilbert space is an active area of research. == Important code families == The first QECC, named after Peter Shor, can be generalized as a [ [ d 2 , 1 , d ] ] {\displaystyle [[d^{2},1,d]]} code, which


id: quantum-error-correction-20260505-2
file: data/en.wikipedia.org/wiki/Quantum_error_correction-2.md
category: reference
title: Quantum error correction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_error_correction
date_saved: 2026-05-05T11:08:16.683136+00:00
instance: kb-cron
parent: quantum-error-correction-20260505-0
summary:
== Classical codes as bias quantum code == Classical error-correcting codes that employ redundancy can be mapped to biased quantum codes that correct either Pauli X (bit-flip) or Pauli Z (phase-flip) errors. The simplest, though inefficient, example is the repetition code. In a repetition code, the logical information is stored as multiple copies of a bit. If these copies are later found to disagree due to errors, the most likely original value is inferred via majority vote. For example, consider a logical bit in the "1" state copied three times. If noise corrupts one of the three bits, leaving the other two unchanged, the most likely scenario is that a single-bit error occurred, and the original logical value was "1." While it is possible that two bits flip, producing three zeros, this outcome is less probable. In this example, the logical information is the single bit, and the three copies are the physical representation. Repetition codes work in classical channels because classical bits can be freely measured and duplicated. In quantum channels, however, the no-cloning theorem prevents copying an unknown qubit, seemingly posing an obstacle to quantum error correction. This challenge is overcome by encoding the logical information of a


id: quantum-error-correction-20260505-3
file: data/en.wikipedia.org/wiki/Quantum_error_correction-3.md
category: reference
title: Quantum error correction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_error_correction
date_saved: 2026-05-05T11:08:16.683136+00:00
instance: kb-cron
parent: quantum-error-correction-20260505-0
summary:
E corr ( ρ ) = P 0 ρ P 0 + ∑ i = 1 3 X i P i ρ P i X i . {\displaystyle {\mathcal {E}}_{\operatorname {corr} }(\rho )=P_{0}\rho P_{0}+\sum _{i=1}^{3}X_{i}P_{i}\rho \,P_{i}X_{i}.} Note that, while this procedure perfectly corrects the output when zero or one flips are introduced by the channel, if more than one qubit is flipped then the output is not properly corrected. For example, if the first and second qubits are flipped, then the syndrome measurement gives the outcome P 3 {\displaystyle P_{3}} , and the third qubit is flipped, instead of the first two. To assess the performance of this error-correcting scheme for a general input we can study the fidelity F ( ψ ′ ) {\displaystyle F(\psi ')} between the input | ψ ′ ⟩ {\displaystyle \vert \psi '\rangle } and the output ρ out ≡ E corr ( E ( | ψ ′ ⟩ ⟨ ψ ′ | ) ) {\displaystyle \rho _{\operatorname {out} }\equiv {\mathcal {E}}_{\operatorname {corr} }({\mathcal {E}}(\vert \psi '\rangle \langle \psi '\vert ))} . Being the output state ρ out {\displaystyle \rho _{\operatorname {out} }} correct when no more than one qubit is flipped, which happens with


id: quantum-error-correction-20260505-4
file: data/en.wikipedia.org/wiki/Quantum_error_correction-4.md
category: reference
title: Quantum error correction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_error_correction
date_saved: 2026-05-05T11:08:16.683136+00:00
instance: kb-cron
parent: quantum-error-correction-20260505-0
summary:
If a bit flip error happens to a qubit, the syndrome analysis will be performed on each block of qubits (1,2,3), (4,5,6), and (7,8,9) to detect and correct at most one bit flip error in each block. If the three bit flip group (1,2,3), (4,5,6), and (7,8,9) are considered as three inputs, then the Shor code circuit can be reduced as a sign flip code. This means that the Shor code can also repair a sign flip error for a single qubit. The Shor code also can correct for any arbitrary errors (both bit flip and sign flip) to a single qubit. If an error is modeled by a unitary transform U, which will act on a qubit | ψ ⟩ {\displaystyle |\psi \rangle } , then U {\displaystyle U} can be described in the form U = c 0 I + c 1 X + c 2 Y + c 3 Z {\displaystyle U=c_{0}I+c_{1}X+c_{2}Y+c_{3}Z} where c 0 {\displaystyle c_{0}} , c 1 {\displaystyle c_{1}} , c 2 {\displaystyle c_{2}} , and c 3 {\displaystyle c_{3}} are complex constants, I is the identity, and the Pauli matrices are given by X = ( 0 1 1 0 ) ; Y


id: quantum-error-correction-20260505-5
file: data/en.wikipedia.org/wiki/Quantum_error_correction-5.md
category: reference
title: Quantum error correction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_error_correction
date_saved: 2026-05-05T11:08:16.683136+00:00
instance: kb-cron
parent: quantum-error-correction-20260505-0
summary:
and it remains maximal. Thus, even without an error correction step, the metrological properties remain the same. (See the Supplement E in Ref., and Ref.) == Experimental realization == There have been several experimental realizations of CSS-based codes. The first demonstration was with nuclear magnetic resonance qubits. Subsequently, demonstrations have been made with linear optics, trapped ions, and superconducting (transmon) qubits. In 2016 for the first time the lifetime of a quantum bit was prolonged by employing a QEC code. The error-correction demonstration was performed on Schrödinger-cat states encoded in a superconducting resonator, and employed a quantum controller capable of performing real-time feedback operations including read-out of the quantum information, its analysis, and the correction of its detected errors. The work demonstrated how the quantum-error-corrected system reaches the break-even point at which the lifetime of a logical qubit exceeds the lifetime of the underlying constituents of the system (the physical qubits). Other error correcting codes have also been implemented, such as one aimed at correcting for photon loss, the dominant error source in photonic qubit schemes. In 2021, an entangling gate between two logical qubits encoded in topological quantum error-correction codes has first been realized using 10 ions in a


id: quantum-experiments-using-satellite-technology-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_Experiments_using_Satellite_Technology-0.md
category: reference
title: Quantum Experiments using Satellite Technology
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_Experiments_using_Satellite_Technology
date_saved: 2026-05-05T11:08:17.875461+00:00
instance: kb-cron
parent: quantum-experiments-using-satellite-technology-20260505-0
summary:
Quantum Experiment using Satellite Technology was launched in 2017 by the Raman Research Institute. In February 2021, the project demonstrated quantum communication for 50 m apart, and on 19 March 2021 for 300 m apart inline of sight in the Space Applications Centre, which was done in coordination with the Indian Space Research Organisation, Indian Institute of Science and Tata Institute of Fundamental Research. Quantum Experiment using Satellite Technology is India's first project on satellite based long distance quantum communication. == Technical specifications == Indigenously developed NAVIC receiver for time synchronization Gimbal mechanism system instead of large aperture telescope for optical alignment. Shared quantum secure text. Shared image transmission. Quantum assisted two ways video conferencing at the Space Applications Centre and Physical Research Laboratory It used robust and high brightness entangled photon source, used BBM92 protocol implementation NAVIC enabled synchronization polarization compensation technique. It is hack proof as it uses quantum key distribution. It uses quantum cryptography and carried out by Quantum information and computing (QuIC) lab . == References ==


