View source for Quantum computing

{{Short description|Computer hardware technology that uses quantum mechanics}}
[[File:Layered Model of Quantum Computing.png|thumb|Layered Model of Quantum Computing]]
[[File:Bloch sphere.svg|thumb|[[Wikipedia:Bloch sphere|Bloch sphere]] representation of a qubit. The state <math>| \psi \rangle = \alpha |0 \rangle + \beta |1 \rangle</math>is a point on the surface of the sphere, partway between the poles, <math>|0\rangle</math> and <math>|1\rangle</math>.]]

A '''quantum computer''' is a (real or theoretical) [[Computer|computer]] that exploits [[Physics:Quantum superposition|superposed]] and [[Quantum entanglement|entangled]] [[Physics:Quantum state|states]]. Quantum computers can be viewed as sampling from quantum systems that evolve in ways that may be described as operating on an enormous number of possibilities simultaneously, though still subject to strict computational constraints. By contrast, ordinary ("classical") computers operate according to deterministic rules. (A [[Computer#Modern computers|classical computer]] can, in principle, be replicated by a [[Turing machine|classical mechanical device]], with only a simple multiple of time cost. On the other hand (it is believed), a quantum computer would require [[Exponential growth|exponentially]] more time and energy to be simulated classically.) 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 [[Post-quantum cryptography|break some widely used public-key cryptographic schemes]] and aid physicists in performing [[Quantum simulator|physical simulations]]. However, current hardware implementations of quantum computation are largely experimental and only suitable for specialized tasks.

<!-- Basic principles of quantum computing-->
The basic unit of information in quantum computing, the [[Qubit|qubit]] (or "quantum bit"), serves the same function as the [[Bit|bit]] in ordinary or "classical" computing.{{sfn|Mermin|2007|p=1}} However, unlike a classical bit, which can be in one of two states (a [[Binary number|binary]]), a qubit can exist in a [[Linear combination|linear combination]] of two states known as a [[Physics:Quantum superposition|quantum superposition]]. The result of [[Physics:Measurement in quantum mechanics|measuring]] a qubit is one of the two states given by a [[Physics:Born rule|probabilistic rule]]. If a quantum computer manipulates the qubit in a particular way, [[Physics:Wave interference|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.

<!--Physical implementations-->
Quantum computers are not yet practical for real-world applications. Physically engineering high-quality qubits has proven to be challenging. If a physical qubit is not sufficiently [[Physics:Isolated system|isolated]] from its environment, it suffers from [[Physics:Quantum decoherence|quantum decoherence]], introducing [[Noise (signal processing)|noise]] into calculations. National governments have invested heavily in experimental research aimed at developing scalable qubits with longer coherence times and lower error rates. Example implementations include [[Superconducting quantum computing|superconductors]] (which isolate an electrical current by eliminating [[Physics:Electrical resistance|electrical resistance]]) and [[Trapped ion quantum computer|ion traps]] (which confine a single [[Atom|atomic particle]] using electromagnetic fields). Researchers have claimed, and are widely believed to be correct, that certain quantum devices can outperform classical computers on narrowly defined tasks, a milestone referred to as quantum advantage or [[Quantum supremacy|quantum supremacy]]. These tasks are not necessarily useful for real-world applications.

== History ==

For many years, the fields of [[Physics:Quantum mechanics|quantum mechanics]] and [[Computer science|computer science]] formed distinct academic communities.{{sfn|Aaronson|2013|p=132}} Modern quantum theory was developed in the 1920s to explain perplexing physical phenomena observed at atomic scales,<ref name="Zwiebach2022">{{cite book|first=Barton |last=Zwiebach |title=Mastering Quantum Mechanics: Essentials, Theory, and Applications |publisher=MIT Press |year=2022 |isbn=978-0-262-04613-8 |at=§1 |quote=Quantum physics has replaced classical physics as the correct fundamental description of our physical universe. It is used routinely to describe most phenomena that occur at short distances. [...] The era of quantum physics began in earnest in 1925 with the discoveries of Erwin Schrödinger and Werner Heisenberg. The seeds for these discoveries were planted by Max Planck, Albert Einstein, Niels Bohr, Louis de Broglie, and others.}}</ref><ref>{{cite book|first=Steven |last=Weinberg |author-link=Steven Weinberg |title=Lectures on Quantum Mechanics |year=2015 |publisher=Cambridge University Press |edition=2nd |isbn=978-1-107-11166-0|chapter=Historical Introduction |pages=1–30}}</ref> and digital computers emerged in the following decades to replace human computers for tedious calculations.<ref>{{Cite book |last=Ceruzzi |first=Paul E. |title=Computing: A Concise History |date=2012 |isbn=978-0-262-31038-3 |publisher=MIT Press |location=Cambridge, Massachusetts |pages=3, 46 |language=en-US |oclc=796812982}}</ref> Both disciplines had practical applications during [[Social:World War II|World War II]]; computers played a major role in wartime cryptography,<ref>{{Cite book |last=Hodges |first=Andrew |author-link=Andrew Hodges |title=Alan Turing: The Enigma |publisher=Princeton University Press |year=2014 |isbn=978-0-691-16472-4 |location=Princeton, New Jersey |page=xviii |language=en-US}}</ref> and quantum physics was essential for [[Physics:Nuclear physics|nuclear physics]] used in the [[Physics:Manhattan Project|Manhattan Project]].<ref>{{Cite journal |last=Mårtensson-Pendrill |first=Ann-Marie |date=2006-11-01 |title=The Manhattan project—a part of physics history |journal=Physics Education |language=en-US |volume=41 |issue=6 |pages=493–501 |bibcode=2006PhyEd..41..493M |doi=10.1088/0031-9120/41/6/001 |issn=0031-9120 |s2cid=120294023}}</ref>

As physicists applied quantum mechanical models to computational problems and swapped digital [[Bit|bit]]s for qubits, the fields of quantum mechanics and computer science began to converge. In 1980, [[Biography:Paul Benioff|Paul Benioff]] introduced the [[Quantum Turing machine|quantum Turing machine]], which uses quantum theory to describe a simplified computer.<ref name="The computer as a physical system">{{cite journal|last1=Benioff|first1=Paul |year=1980|title=The computer as a physical system: A microscopic quantum mechanical Hamiltonian model of computers as represented by Turing machines|journal=Journal of Statistical Physics|volume=22|issue=5|pages=563–591|bibcode=1980JSP....22..563B|doi=10.1007/bf01011339|s2cid=122949592}}</ref>
When digital computers became faster, physicists faced an exponential increase in overhead when simulating quantum dynamics,<ref>{{Cite journal |last1=Buluta |first1=Iulia |last2=Nori |first2=Franco |date=2009-10-02 |title=Quantum Simulators |journal=Science |language=en |volume=326 |issue=5949 |pages=108–111 |doi=10.1126/science.1177838 |pmid=19797653 |bibcode=2009Sci...326..108B |s2cid=17187000 |issn=0036-8075}}</ref> prompting [[Biography:Yuri Manin|Yuri Manin]] and [[Biography:Richard Feynman|Richard Feynman]] to independently suggest that hardware based on quantum phenomena might be more efficient for computer simulation.<ref name="manin1980vychislimoe">{{cite book |author=Manin |first=Yu. I. |url=http://publ.lib.ru/ARCHIVES/M/MANIN_Yuriy_Ivanovich/Manin_Yu.I._Vychislimoe_i_nevychislimoe.(1980).%5bdjv-fax%5d.zip |title=Vychislimoe i nevychislimoe |publisher=Soviet Radio |year=1980 |pages=13–15 |language=ru |trans-title=Computable and Noncomputable |access-date=4 March 2013 |archive-url=https://web.archive.org/web/20130510173823/http://publ.lib.ru/ARCHIVES/M/MANIN_Yuriy_Ivanovich/Manin_Yu.I._Vychislimoe_i_nevychislimoe.(1980).%5Bdjv%5D.zip |archive-date=10 May 2013 }}</ref><ref>{{cite journal |last1=Feynman |first1=Richard |author-link=Richard Feynman |title=Simulating Physics with Computers |journal=International Journal of Theoretical Physics |date=June 1982 |volume=21 |issue=6/7 |pages=467–488 |doi=10.1007/BF02650179 |url=https://people.eecs.berkeley.edu/~christos/classics/Feynman.pdf |access-date=28 February 2019 |bibcode=1982IJTP...21..467F |s2cid=124545445 |archive-url=https://web.archive.org/web/20190108115138/https://people.eecs.berkeley.edu/~christos/classics/Feynman.pdf |archive-date=8 January 2019 }}</ref>{{sfn|Nielsen|Chuang|2010|p=214}}
In a 1984 paper, [[Biography:Charles H. Bennett (physicist)|Charles Bennett]] and [[Biography:Gilles Brassard|Gilles Brassard]] applied quantum theory to [[Cryptography|cryptography]] protocols and demonstrated that quantum key distribution could enhance [[Information security|information security]].<ref name="bb84">{{cite book|first1=C. H. |last1=Bennett |first2=G. |last2=Brassard |chapter=Quantum cryptography: Public key distribution and coin tossing |title=Proceedings of the International Conference on Computers, Systems & Signal Processing, Bangalore, India |volume=1 |pages=175–179 |publisher=IEEE |year=1984 |location=New York }} Reprinted as {{cite journal|first1=C. H. |last1=Bennett |first2=G. |last2=Brassard |title=Quantum cryptography: Public key distribution and coin tossing |journal=Theoretical Computer Science |series=Theoretical Aspects of Quantum Cryptography – celebrating 30 years of BB84 |volume=560 |number=1 |date=4 December 2014 |pages=7–11 |doi=10.1016/j.tcs.2014.05.025 |doi-access=free|arxiv=2003.06557 |bibcode=2014TComS.560....7B }}</ref><ref name="personal">{{Cite book |last=Brassard |first=G. |title=IEEE Information Theory Workshop on Theory and Practice in Information-Theoretic Security, 2005 |chapter=Brief history of quantum cryptography: A personal perspective |date=2005 |location=Awaji Island, Japan |publisher=IEEE |pages=19–23 |doi=10.1109/ITWTPI.2005.1543949 |arxiv=quant-ph/0604072 |isbn=978-0-7803-9491-9|s2cid=16118245 }}</ref>

[[Quantum algorithm]]s then emerged for solving [[Oracle machine|oracle problems]], such as Deutsch's algorithm in 1985,<ref>{{Cite journal |date=1985-07-08 |title=Quantum theory, the Church–Turing principle and the universal quantum computer |journal=Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences |language=en |volume=400 |issue=1818 |pages=97–117 |doi=10.1098/rspa.1985.0070 |bibcode=1985RSPSA.400...97D |s2cid=1438116 |issn=0080-4630|last1=Deutsch |first1=D. }}</ref> the Bernstein{{en dash}}Vazirani algorithm in 1993,<ref>{{Cite book |last1=Bernstein |first1=Ethan |title=Proceedings of the twenty-fifth annual ACM symposium on Theory of computing – STOC '93 |last2=Vazirani |first2=Umesh |date=1993 |publisher=ACM Press |isbn=978-0-89791-591-5 |location=San Diego, California, United States |pages=11–20 |language=en |chapter=Quantum complexity theory |doi=10.1145/167088.167097 |chapter-url=http://portal.acm.org/citation.cfm?doid=167088.167097 |s2cid=676378}}</ref> and Simon's algorithm in 1994.<ref>{{Cite book |last=Simon |first=D. R. |title=Proceedings 35th Annual Symposium on Foundations of Computer Science |chapter=On the power of quantum computation |date=1994 |location=Santa Fe, New Mexico, USA |publisher=IEEE Comput. Soc. Press |pages=116–123 |doi=10.1109/SFCS.1994.365701 |isbn=978-0-8186-6580-6 |s2cid=7457814}}</ref>
These algorithms did not solve practical problems, but demonstrated mathematically that one could obtain more information by querying a [[Black box|black box]] with a quantum state in [[Physics:Quantum superposition|superposition]], sometimes referred to as ''quantum parallelism''.{{sfn|Nielsen|Chuang|2010|p=30-32}}

[[File:Peter Shor 2017 Dirac Medal Award Ceremony.png|thumb|[[Biography:Peter Shor|Peter Shor]] (pictured here in 2017) showed in 1994 that a scalable quantum computer would be able to break RSA encryption.|upright=0.9]]
[[Biography:Peter Shor|Peter Shor]] built on these results with [[Shor's algorithm|his 1994 algorithm]] for breaking the widely used [[RSA (cryptosystem)|RSA]] and Diffie{{en dash}}Hellman encryption protocols,{{sfn|Shor|1994}} which drew significant attention to the field of quantum computing. In 1996, [[Grover's algorithm]] established a quantum speedup for the widely applicable [[Unstructured data|unstructured]] search problem.<ref>{{Cite conference |last=Grover |first=Lov K. |date=1996 |title=A fast quantum mechanical algorithm for database search |conference=ACM symposium on Theory of computing |language=en |location=Philadelphia |publisher=ACM Press |pages=212–219 |doi=10.1145/237814.237866 |isbn=978-0-89791-785-8 |arxiv=quant-ph/9605043}}</ref>{{sfn|Nielsen|Chuang|2010 |p=7}} The same year, [[Biography:Seth Lloyd|Seth Lloyd]] proved that quantum computers could simulate quantum systems without the exponential overhead present in classical simulations,<ref name="273.5278.1073">{{Cite journal |last=Lloyd |first=Seth |date=1996-08-23 |title=Universal Quantum Simulators |journal=Science |volume=273 |issue=5278 |pages=1073–1078 |pmid=8688088 |s2cid=43496899 |bibcode=1996Sci...273.1073L |doi=10.1126/science.273.5278.1073 |issn=0036-8075}}</ref> validating Feynman's 1982 conjecture.<ref>{{Cite journal |last1=Cao |first1=Yudong |last2=Romero |first2=Jonathan |last3=Olson |first3=Jonathan P. |last4=Degroote |first4=Matthias |last5=Johnson |first5=Peter D. |last6=Kieferová |first6=Mária |last7=Kivlichan |first7=Ian D. |last8=Menke |first8=Tim |last9=Peropadre |first9=Borja |last10=Sawaya |first10=Nicolas P. D. |last11=Sim |first11=Sukin |last12=Veis |first12=Libor |last13=Aspuru-Guzik |first13=Alán |date=2019-10-09 |title=Quantum Chemistry in the Age of Quantum Computing |journal=Chemical Reviews |language=en-US |volume=119 |issue=19 |pages=10856–10915 |arxiv=1812.09976 |doi=10.1021/acs.chemrev.8b00803 |issn=0009-2665 |pmid=31469277 |s2cid=119417908 |display-authors=5 |bibcode=2019ChRv..11910856C }}</ref>

Over the years, [[Physics:Experimental physics|experimentalists]] have constructed small-scale quantum computers using [[Trapped ion quantum computer|trapped ions]] and superconductors.{{sfn|Grumbling|Horowitz|2019|pp=164-169}}
In 1998, a two-qubit quantum computer demonstrated the feasibility of the technology,<ref>{{cite journal |last1=Chuang |first1=Isaac L. |last2=Gershenfeld |first2=Neil |last3=Kubinec |first3=Markdoi |date=April 1998 |title=Experimental Implementation of Fast Quantum Searching |journal=Physical Review Letters |publisher=[[Organization:American Physical Society|American Physical Society]] |volume=80 |issue=15 |pages=3408–3411 |bibcode=1998PhRvL..80.3408C |doi=10.1103/PhysRevLett.80.3408}}</ref><ref>{{cite news |last=Holton |first=William Coffeen |title=quantum computer |url=https://www.britannica.com/technology/quantum-computer |access-date=4 Dec 2021 |newspaper=Encyclopedia Britannica |publisher=[[Encyclopædia Britannica]]}}</ref> and subsequent experiments have increased the number of qubits and reduced error rates.{{sfn|Grumbling|Horowitz|2019 |pp=164-169}}

In 2019, [[Company:Google AI|Google AI]] and [[Organization:NASA|NASA]] announced that they had achieved [[Quantum supremacy|quantum supremacy]] with a 54-qubit machine, performing a computation that any classical computer would find impossible.<ref>{{Cite journal |last=Gibney |first=Elizabeth |date=2019-10-23 |title=Hello quantum world! Google publishes landmark quantum supremacy claim |journal=Nature |language=en |volume=574 |issue=7779 |pages=461–462 |doi=10.1038/d41586-019-03213-z |pmid=31645740 |bibcode=2019Natur.574..461G |doi-access=free}}</ref><ref name="1910.11333">Lay summary: {{cite journal |url=https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html |title=Quantum Supremacy Using a Programmable Superconducting Processor |journal=Nature |publisher=[[Company:Google AI|Google AI]] |first1=John |last1=Martinis |first2=Sergio |last2=Boixo |date=October 23, 2019 |volume=574 |issue=7779 |pages=505–510 |doi=10.1038/s41586-019-1666-5 |pmid=31645734 |arxiv=1910.11333 |bibcode=2019Natur.574..505A |s2cid=204836822 |access-date=2022-04-27}}<br />{{*}}Journal article: {{cite journal |last1=Arute |first1=Frank |last2=Arya |first2=Kunal |last3=Babbush |first3=Ryan |last4=Bacon |first4=Dave |last5=Bardin |first5=Joseph C. |last6=Barends |first6=Rami |last7=Biswas |first7=Rupak |last8=Boixo |first8=Sergio |last9=Brandao |first9=Fernando G. S. L. |last10=Buell |first10=David A. |last11=Burkett |first11=Brian |first15=Roberto |first57=Murphy Yuezhen |last64=Rubin |first63=Pedram |last63=Roushan |first62=Eleanor G. |last62=Rieffel |first61=Chris |last61=Quintana |first60=John C. |last60=Platt |first59=Andre |last59=Petukhov |first58=Eric |last58=Ostby |last57=Niu |last65=Sank |first56=Charles |last56=Neill |first55=Matthew |last55=Neeley |first54=Ofer |last54=Naaman |first53=Josh |last53=Mutus |first52=Masoud |last52=Mohseni |first51=Kristel |last51=Michielsen |first50=Xiao |last50=Mi |first64=Nicholas C. |first65=Daniel |last49=Megrant |last74=Yeh |last12=Chen |first12=Yu |last13=Chen |first13=Zijun |last14=Chiaro |first14=Ben |first77=John M. |last77=Martinis |first76=Hartmut |last76=Neven |first75=Adam |last75=Zalcman |first74=Ping |first73=Z. Jamie |last66=Satzinger |last73=Yao |first72=Theodore |last72=White |first71=Benjamin |last71=Villalonga |first70=Amit |last70=Vainsencher |first69=Matthew D. |last69=Trevithick |first68=Kevin J. |last68=Sung |first67=Vadim |last67=Smelyanskiy |first66=Kevin J. |first49=Anthony |first48=Matthew |last16=Courtney |last24=Guerin |first30=Trent |last30=Huang |first29=Markus |last29=Hoffman |first28=Alan |last28=Ho |first27=Michael J. |last27=Hartmann |first26=Matthew P. |last26=Harrigan |first25=Steve |last25=Habegger |first24=Keith |first23=Rob |first31=Travis S. |last23=Graff |first22=Marissa |last22=Giustina |first21=Craig |last21=Gidney |first20=Austin |last20=Fowler |first19=Brooks|last19=Foxen |first18=Edward |last18=Farhi |first17=Andrew |last17=Dunsworsth |first16=William |last31=Humble |last32=Isakov |last48=McEwen |first40=Alexander |first47=Jarrod R. |last47=McClean |first46=Salvatore |last46=Mandrà |first45=Dmitry |last45=Lyakh |first44=Erik |last44=Lucero |first43=Mike |last43=Lindmark |first42=David |last42=Landhuis |first41=Fedor |last15=Collins |last40=Korotov |first32=Sergei V. |first39=Sergey |last39=Knysh |first38=Paul V. |last38=Klimov |first37=Julian |last37=Kelly |first36=Kostyantyn |last36=Kechedzhi |first35=Dvir |last35=Kafri |first34=Zhang |last34=Jiang |first33=Evan |last33=Jeffery |last41=Kostritsa |display-authors=5 |title=Quantum supremacy using a programmable superconducting processor |journal=Nature |date=October 23, 2019 |volume=574 |issue=7779 |pages=505–510 |doi=10.1038/s41586-019-1666-5 |pmid=31645734 |arxiv=1910.11333 |bibcode=2019Natur.574..505A |s2cid=204836822}}</ref><ref>{{Cite news |last=Aaronson |first=Scott |date=2019-10-30 |title=Opinion {{!}} Why Google's Quantum Supremacy Milestone Matters |url=https://www.nytimes.com/2019/10/30/opinion/google-quantum-computer-sycamore.html |access-date=2021-09-25 |work=The New York Times |issn=0362-4331}}</ref><ref>{{cite arXiv |last1=Pan |first1=Feng |last2=Zhang |first2=Pan |date=2021-03-04 |title=Simulating the Sycamore quantum supremacy circuits |class=quant-ph |eprint=2103.03074}}</ref>

This announcement was met with a rebuttal from [[Company:IBM|IBM]], which contended that the calculation Google claimed would take 10,000 years could be performed in just 2.5 days on its  Summit supercomputer if its architecture were optimized, sparking a debate over the precise threshold for "quantum supremacy".<ref>{{Cite news |last=Sample |first=Ian |date=2019-10-23 |title=Google claims it has achieved 'quantum supremacy' – but IBM disagrees |url=https://www.theguardian.com/technology/2019/oct/23/google-claims-it-has-achieved-quantum-supremacy-but-ibm-disagrees |access-date=2025-08-01 |work=The Guardian |language=en-GB |issn=0261-3077}}</ref>

== Quantum information processing ==

[[Computer engineering|Computer engineers]] typically describe a modern computer's operation in terms of [[Physics:Classical electromagnetism|classical electrodynamics]]. In these "classical" computers, some components (such as [[Physics:Semiconductor|semiconductors]] and [[Random number generation|random number generators]]) may rely on quantum behavior; however, because they are not [[Physics:Isolated system|isolated]] from their environment, any [[Quantum information|quantum information]] eventually quickly [[Physics:Quantum decoherence|decoheres]]. While [[Programmer|programmers]] may depend on [[Probability theory|probability theory]] when designing a [[Randomized algorithm|randomized algorithm]], quantum-mechanical notions such as [[Linear combination|superposition]] and [[Physics:Wave interference|wave interference]] are largely irrelevant in [[Program analysis|program analysis]].

[[Quantum programming|Quantum programs]], in contrast, rely on precise control of coherent quantum systems. Physicists [[Physics:Mathematical formulation of quantum mechanics|describe these systems mathematically]] using [[Linear algebra|linear algebra]]. [[Complex number]]s model [[Physics:Probability amplitude|probability amplitude]]s, [[Vector (mathematics and physics)|vectors]] model [[Physics:Quantum state|quantum state]]s, and [[Matrix (mathematics)|matrices]] model the operations that can be performed on these states. Programming a quantum computer is then a matter of [[Function composition (computer science)|composing]] operations in such a way that the resulting program computes a useful result in theory and is implementable in practice.

As physicist [[Biography:Charles H. Bennett (physicist)|Charlie Bennett]] describes the relationship between quantum and classical computers,<ref>{{Cite AV media |url=https://www.youtube.com/live/rslt-LwtDK4&t=4102 |title=Information Is Quantum: How Physics Helped Explain the Nature of Information and What Can Be Done With It |date=2020-07-31 |last=Bennett |first=Charlie |type=Videotape |time=1:08:22 |via=YouTube}}</ref>
{{Blockquote|text=A classical computer is a quantum computer&nbsp;... so we shouldn't be asking about "where do quantum speedups come from?" We should say, "Well, all computers are quantum.&nbsp;... Where do classical slowdowns come from?"}}

=== Quantum information ===
Just as the bit is the basic concept of classical information theory, the ''[[Qubit|qubit]]'' is the fundamental unit of [[Quantum information|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 <math>|0\rangle</math> and <math>|1\rangle</math>, serve as the quantum counterparts of the classical states 0 and 1. However, the quantum states <math>|0\rangle</math> and <math>|1\rangle</math> belong to a [[Vector space|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 <math>|0\rangle</math> and <math>|1\rangle</math>.{{sfn|Nielsen|Chuang|2010|page=13}}{{sfn|Mermin|2007|p=17}}

A two-dimensional [[Vector (mathematics and physics)|vector]] mathematically represents a qubit state. Physicists typically use [[Bra–ket notation|bra–ket notation]] for quantum mechanical [[Linear algebra|linear algebra]], writing <math>|\psi\rangle</math> {{gloss|ket psi}} for a vector labeled <math>\psi</math>. Because a qubit is a two-state system, any qubit state takes the form <math>\alpha|0\rangle+\beta|1\rangle</math>, where <math>|0\rangle</math> and <math>|1\rangle</math> are the standard ''basis states'',{{efn|The [[Standard basis|standard basis]] is also the ''computational basis''.{{sfn|Mermin|2007|p=18}}}} and <math>\alpha</math> and <math>\beta</math> are the ''[[Physics:Probability amplitude|probability amplitude]]s,'' which are in general complex numbers.{{sfn|Mermin|2007|p=17}} If either <math>\alpha</math> or <math>\beta</math> is zero, the qubit is effectively a classical bit; when both are nonzero, the qubit is in superposition. Such a quantum state vector behaves similarly to a (classical) [[Probability vector|probability vector]], with one key difference: unlike probabilities, probability {{em|amplitudes}} are not necessarily positive numbers.{{sfn|Aaronson|2013|page=110}} Negative amplitudes allow for destructive wave interference.

When a qubit is [[Physics:Quantum measurement|measured]] in the [[Standard basis|standard basis]], the result is a classical bit. The [[Physics:Born rule|Born rule]] describes the norm-squared correspondence between amplitudes and probabilities{{mdash}}when measuring a qubit <math>\alpha|0\rangle+\beta|1\rangle</math>, the state [[Physics:Wave function collapse|collapses]] to <math>|0\rangle</math> with probability <math>|\alpha|^2</math>, or to <math>|1\rangle</math> with probability <math>|\beta|^2</math>.
Any valid qubit state has coefficients <math>\alpha</math> and <math>\beta</math> such that <math>|\alpha|^2+|\beta|^2 = 1</math>.
As an example, measuring the qubit <math>1/\sqrt {2}|0\rangle+1/\sqrt{2}|1\rangle</math> would produce either <math>|0\rangle</math> or <math>|1\rangle</math> with equal probability.

Each additional qubit doubles the [[Dimension (vector space)|dimension]] of the [[State space|state space]].{{sfn|Mermin|2007|p=18}}
As an example, the vector {{nowrap|{{sfrac|1|√2}}{{ket|00}} + {{sfrac|1|√2}}{{ket|01}}}} represents a two-qubit state, a [[Tensor product|tensor product]] of the qubit {{ket|0}} with the qubit {{nowrap|{{sfrac|1|√2}}{{ket|0}} + {{sfrac|1|√2}}{{ket|1}}}}.
This vector inhabits a four-dimensional [[Vector space|vector space]] spanned by the basis vectors {{ket|00}}, {{ket|01}}, {{ket|10}}, and {{ket|11}}.
The [[Bell state]] {{nowrap|{{sfrac|1|√2}}{{ket|00}} + {{sfrac|1|√2}}{{ket|11}}}} is impossible to decompose into the tensor product of two individual qubits{{mdash}}the two qubits are ''[[Quantum entanglement|entangled]]'' because neither qubit has a state vector of its own.
In general, the vector space for an ''n''-qubit system is {{math|2{{sup|''n''}}}}-dimensional, and this makes it challenging for a classical computer to simulate a quantum one: representing a 100-qubit system requires storing 2<sup>100</sup> classical values.

=== Unitary operators<span class="anchor" id="gate-application"></span> ===

The state of this one-qubit [[Quantum memory|quantum memory]] can be manipulated by applying [[Quantum logic gate|quantum logic gate]]s, analogous to how classical memory can be manipulated with [[Engineering:Logic gate|classical logic gates]]. One important gate for both classical and quantum computation is the NOT gate, which can be represented by a [[Matrix (mathematics)|matrix]]
<math display="block">X := \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}.</math>
Mathematically, the application of such a logic gate to a quantum state vector is modeled with [[Matrix multiplication|matrix multiplication]]. Thus
: <math>X|0\rangle = |1\rangle</math> and <math>X|1\rangle = |0\rangle</math>.
The mathematics of single-qubit gates can be extended to operate on multi-qubit quantum memories in two important ways. One way is simply to select a qubit and apply that gate to the target qubit while leaving the remainder of the memory unaffected. Another way is to apply the gate to its target only if another part of the memory is in a desired state. These two choices can be illustrated using another example. The possible states of a two-qubit quantum memory are
<math display="block">
 |00\rangle := \begin{pmatrix} 1 \\ 0 \\ 0 \\ 0 \end{pmatrix};\quad
 |01\rangle := \begin{pmatrix} 0 \\ 1 \\ 0 \\ 0 \end{pmatrix};\quad
 |10\rangle := \begin{pmatrix} 0 \\ 0 \\ 1 \\ 0 \end{pmatrix};\quad
 |11\rangle := \begin{pmatrix} 0 \\ 0 \\ 0 \\ 1 \end{pmatrix}.
</math>
The [[Controlled NOT gate|controlled NOT (CNOT)]] gate can then be represented using the following matrix:
<math display="block">
 \operatorname{CNOT} :=
 \begin{pmatrix}
  1 & 0 & 0 & 0 \\
   0 & 1 & 0 & 0 \\
   0 & 0 & 0 & 1 \\
   0 & 0 & 1 & 0
 \end{pmatrix}.
</math>
As a mathematical consequence of this definition, <math display="inline">\operatorname{CNOT}|00\rangle = |00\rangle</math>, <math display="inline">\operatorname{CNOT}|01\rangle = |01\rangle</math>, <math display="inline">\operatorname{CNOT}|10\rangle = |11\rangle</math>, and <math display="inline">\operatorname{CNOT}|11\rangle = |10\rangle</math>. In other words, the CNOT applies a NOT gate (<math display="inline">X</math> from before) to the second qubit if and only if the first qubit is in the state <math display="inline">|1\rangle</math>. If the first qubit is <math display="inline">|0\rangle</math>, nothing is done to either qubit.

In summary, quantum computation can be described as a network of quantum logic gates and measurements. However, any [[Deferred measurement principle|measurement can be deferred]] to the end of quantum computation, though this deferment may come at a computational cost, so most [[Quantum circuit|quantum circuit]]s depict a network consisting only of quantum logic gates and no measurements.

=== Quantum parallelism ===

''Quantum parallelism'' is the heuristic that quantum computers can be thought of as evaluating a function for multiple input values simultaneously. This can be achieved by preparing a quantum system in a superposition of input states and applying a unitary transformation that encodes the function to be evaluated. The resulting state encodes the function's output values for all input values in the superposition, enabling the simultaneous computation of multiple outputs. This property is key to the speedup of many quantum algorithms. However, "parallelism" in this sense is insufficient to speed up a computation, because the measurement at the end of the computation gives only one value. To be useful, a quantum algorithm must also incorporate some other conceptual ingredient.{{sfn|Nielsen|Chuang|2010|p=30–32}}{{sfn|Mermin|2007|pp=38–39}}

=== Quantum programming<span class="anchor" id="Models of computation for quantum computing"></span> ===

There are multiple [[Model of computation|models of computation]] for quantum computing, distinguished by the basic elements in which the computation is decomposed.

==== Gate array {{anchor|Quantum circuit|Definition}} ====
[[File:Quantum Toffoli Gate Implementation.svg|thumb|A quantum circuit diagram implementing a [[Toffoli gate]] from [[Quantum logic gate|more primitive gates]]|upright=1.15]]

A [[Quantum circuit|quantum gate array]] decomposes computation into a sequence of few-qubit quantum gates. A 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 logic gates and no measurements.

Any quantum computation (which is, in the above formalism, any [[Unitary matrix|unitary matrix]] of size <math>2^n \times 2^n</math> over <math>n</math> qubits) can be represented as a network of quantum logic gates from a fairly small family of gates. A choice of gate family that enables this construction is known as a [[Quantum logic gate#Universal quantum gates|universal gate set]], since a computer that can run such circuits is a universal quantum computer. One common such set includes all single-qubit gates as well as the CNOT gate from above. This means any quantum computation can be performed by executing a sequence of single-qubit gates together with CNOT gates. Though this gate set is infinite, it can be replaced with a finite gate set by appealing to the [[Solovay–Kitaev theorem|Solovay-Kitaev theorem]]. Implementation of Boolean functions using the few-qubit quantum gates is presented here.<ref>{{Cite book |last1=Kurgalin |first1=Sergei |title=Concise guide to quantum computing: algorithms, exercises, and implementations |last2=Borzunov |first2=Sergei |date=2021 |publisher=Springer |isbn=978-3-030-65054-4 |series=Texts in computer science |location=Cham}}</ref>

==== Measurement-based quantum computing ====

A measurement-based quantum computer decomposes computation into a sequence of [[Bell state#Bell state measurement|Bell state measurements]] and single-qubit quantum gates applied to a highly entangled initial state (a [[Cluster state|cluster state]]), using a technique called [[Quantum gate teleportation|quantum gate teleportation]].

==== Adiabatic quantum computing ====

An [[Physics:Adiabatic quantum computation|adiabatic quantum computer]], based on [[Quantum annealing|quantum annealing]], decomposes computation into a slow continuous transformation of an initial [[Physics:Hamiltonian (quantum mechanics)|Hamiltonian]] into a final Hamiltonian, whose ground states contain the solution.<ref name="Das 2008 1061–1081">{{cite journal|last1=Das|first1=A.|last2=Chakrabarti|first2=B. K.|year=2008|title=Quantum Annealing and Analog Quantum Computation|journal=[[Physics:Reviews of Modern Physics|Rev. Mod. Phys.]]|volume=80|issue=3|pages=1061–1081|arxiv=0801.2193|bibcode=2008RvMP...80.1061D|citeseerx=10.1.1.563.9990|doi=10.1103/RevModPhys.80.1061|s2cid=14255125}}</ref>

==== Neuromorphic quantum computing ====
Neuromorphic quantum computing (abbreviated 'n.quantum computing') is an unconventional process of computing that uses [[Neuromorphic engineering|neuromorphic computing]] to perform quantum operations. It was suggested that quantum algorithms, which are algorithms that run on a realistic model of quantum computation, can be computed equally efficiently with neuromorphic quantum computing. Both traditional quantum computing and neuromorphic quantum computing are physics-based unconventional computing approaches to computations and do not follow the [[Von Neumann architecture|von Neumann architecture]]. They both construct a system (a circuit) that represents the physical problem at hand and then leverage their respective physics properties of the system to seek the "minimum". Neuromorphic quantum computing and quantum computing share similar physical properties during computation.

==== Topological quantum computing ====

A [[Topological quantum computer|topological quantum computer]] decomposes computation into the braiding of [[Anyon|anyon]]s in a 2D lattice.<ref name="Nayaketal2008">{{cite journal |last1=Nayak |first1=Chetan |last2=Simon |first2=Steven |last3=Stern |first3=Ady |last4=Das Sarma |first4=Sankar |year=2008 |title=Nonabelian Anyons and Quantum Computation |journal=Reviews of Modern Physics |volume=80 |issue=3 |pages=1083–1159 |arxiv=0707.1889 |bibcode=2008RvMP...80.1083N |doi=10.1103/RevModPhys.80.1083 |s2cid=119628297}}</ref>

==== Quantum Turing machine ====

A [[Quantum Turing machine|quantum Turing machine]] is the quantum analog of a [[Turing machine]].<ref name="The computer as a physical system"/> All of these models of computation—quantum circuits,<ref name="quantum circuits">{{Cite book|last=Chi-Chih Yao|first=A.|title=Proceedings of 1993 IEEE 34th Annual Foundations of Computer Science |chapter=Quantum circuit complexity |year=1993|pages=352–361|doi=10.1109/SFCS.1993.366852|isbn=0-8186-4370-6|s2cid=195866146}}</ref> [[One-way quantum computer|one-way quantum computation]],<ref>{{Cite journal |last1=Raussendorf |first1=Robert |last2=Browne |first2=Daniel E. |last3=Briegel |first3=Hans J. |date=2003-08-25 |title=Measurement-based quantum computation on cluster states |journal=Physical Review A |volume=68 |issue=2 |article-number=022312 |doi=10.1103/PhysRevA.68.022312 |arxiv=quant-ph/0301052 |bibcode=2003PhRvA..68b2312R |s2cid=6197709}}</ref> adiabatic quantum computation,<ref>{{Cite journal |last1=Aharonov |first1=Dorit |last2=van Dam |first2=Wim |last3=Kempe |first3=Julia |last4=Landau |first4=Zeph |last5=Lloyd |first5=Seth |last6=Regev |first6=Oded |date=2008-01-01 |title=Adiabatic Quantum Computation Is Equivalent to Standard Quantum Computation |journal=SIAM Review |volume=50 |issue=4 |pages=755–787 |doi=10.1137/080734479 |arxiv=quant-ph/0405098 |bibcode=2008SIAMR..50..755A |s2cid=1503123 |issn=0036-1445}}</ref> and topological quantum computation<ref name="FLW02">{{Cite journal |last1=Freedman |first1=Michael H. |last2=Larsen |first2=Michael |last3=Wang |first3=Zhenghan |date=2002-06-01 |title=A Modular Functor Which is Universal for Quantum Computation |journal=Communications in Mathematical Physics |volume=227 |issue=3 |pages=605–622 |doi=10.1007/s002200200645 |issn=0010-3616 |arxiv=quant-ph/0001108 |bibcode=2002CMaPh.227..605F |s2cid=8990600}}</ref>—have been shown to be equivalent to the quantum Turing machine; given a perfect implementation of one such quantum computer, it can simulate all the others with no more than polynomial overhead. This equivalence need not hold for practical quantum computers, since the overhead of simulation may be too large to be practical.

====Noisy intermediate-scale quantum computing====
The [[Threshold theorem|threshold theorem]] shows how increasing the number of qubits can mitigate errors,{{sfn|Nielsen|Chuang|2010 |p=481}} yet fully fault-tolerant quantum computing remains "a rather distant dream".<ref name="preskill2018"/> According to some researchers, ''noisy intermediate-scale quantum'' (NISQ) machines may have specialized uses in the near future, but [[Noise (signal processing)|noise]] in quantum gates limits their reliability.<ref name="preskill2018">{{Cite journal |last=Preskill |first=John |date=6 August 2018 |title=Quantum Computing in the NISQ era and beyond |journal=Quantum |volume=2 |article-number=79 |arxiv=1801.00862 |doi=10.22331/q-2018-08-06-79 |doi-access=free |bibcode=2018Quant...2...79P |s2cid=44098998}}</ref>
Scientists at [[Organization:Harvard University|Harvard]] University successfully created "quantum circuits" that correct errors more efficiently than alternative methods, which may potentially remove a major obstacle to practical quantum computers.<ref>{{Cite journal |last1=Bluvstein |first1=Dolev |last2=Evered |first2=Simon J. |last3=Geim |first3=Alexandra A. |last4=Li |first4=Sophie H. |last5=Zhou |first5=Hengyun |last6=Manovitz |first6=Tom |last7=Ebadi |first7=Sepehr |last8=Cain |first8=Madelyn |last9=Kalinowski |first9=Marcin |last10=Hangleiter |first10=Dominik |last11=Ataides |first11=J. Pablo Bonilla |last12=Maskara |first12=Nishad |last13=Cong |first13=Iris |last14=Gao |first14=Xun |last15=Rodriguez |first15=Pedro Sales |date=2023-12-06 |title=Logical quantum processor based on reconfigurable atom arrays |journal=Nature |volume=626 |issue=7997 |language=en |pages=58–65 |doi=10.1038/s41586-023-06927-3 |pmid=38056497 |pmc=10830422 |issn=1476-4687|arxiv=2312.03982 |s2cid=266052773 }}</ref> The Harvard research team was supported by [[Organization:Massachusetts Institute of Technology|MIT]], QuEra Computing, [[Organization:California Institute of Technology|Caltech]], and [[Organization:Princeton University|Princeton]] University and funded by DARPA's Optimization with Noisy Intermediate-Scale Quantum devices (ONISQ) program.<ref>{{Cite web |date=December 6, 2023 |title=DARPA-Funded Research Leads to Quantum Computing Breakthrough |url=https://www.darpa.mil/news-events/2023-12-06 |access-date=January 5, 2024 |website=darpa.mil}}</ref><ref>{{Cite web |last=Choudhury |first=Rizwan |date=2023-12-30 |title=Top 7 innovation stories of 2023 – Interesting Engineering |url=https://interestingengineering.com/lists/top-7-innovation-stories-of-2023-interesting-engineering |access-date=2024-01-06 |website=interestingengineering.com |language=en-US}}</ref>

==== Quantum cryptography and cybersecurity ====
{{main|Quantum cryptography}}

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.<ref name=Gisin-2002>{{Cite journal |last1=Gisin |first1=Nicolas |last2=Ribordy |first2=Grégoire |last3=Tittel |first3=Wolfgang |last4=Zbinden |first4=Hugo |date=2002-03-08 |title=Quantum cryptography |url=https://link.aps.org/doi/10.1103/RevModPhys.74.145 |journal=Reviews of Modern Physics |language=en |volume=74 |issue=1 |pages=145–195 |doi=10.1103/RevModPhys.74.145 |issn=0034-6861|arxiv=quant-ph/0101098 |bibcode=2002RvMP...74..145G }}</ref>

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.<ref name=Gisin-2002/>

Ongoing research in quantum and [[Post-quantum cryptography|post-quantum cryptography]] has led to new algorithms for [[Quantum key distribution|quantum key distribution]], initial work on quantum [[Random number generation|random number generation]] and to some early technology demonstrations.<ref name=Pirandola>{{cite journal |last1=Pirandola |first1=S. |last2=Andersen |first2=U. L. |last3=Banchi |first3=L. |last4=Berta |first4=M. |last5=Bunandar |first5=D. |last6=Colbeck |first6=R. |last7=Englund |first7=D. |last8=Gehring |first8=T. |last9=Lupo |first9=C. |last10=Ottaviani |first10=C. |last11=Pereira |first11=J. |last12=Razavi |first12=M. |last13=Shamsul Shaari |first13=J. |last14=Tomamichel |first14=M. |last15=Usenko |first15=V. C. |last16=Vallone |first16=G. |last17=Villoresi |first17=P. |last18=Wallden |first18=P. |year=2020 |title=Advances in quantum cryptography |journal=Advances in Optics and Photonics |volume=12 |issue=4 |page=1012 |doi=10.1364/AOP.361502 |arxiv=1906.01645 |bibcode=2020AdOP...12.1012P}}</ref>{{rp|1012–1036}}

== Communication ==

[[Quantum cryptography]] enables new ways to transmit data securely; for example, [[Quantum key distribution|quantum key distribution]] uses entangled quantum states to establish secure cryptographic keys.<ref name=Pirandola/>{{rp|1017}} When a sender and receiver exchange quantum states, they can guarantee that an [[Adversary (cryptography)|adversary]] does not intercept the message, as any unauthorized eavesdropper would disturb the delicate quantum system and introduce a detectable change.<ref>{{Cite journal |last1=Xu |first1=Feihu |last2=Ma |first2=Xiongfeng |last3=Zhang |first3=Qiang |last4=Lo |first4=Hoi-Kwong |last5=Pan |first5=Jian-Wei |date=2020-05-26 |title=Secure quantum key distribution with realistic devices |journal=Reviews of Modern Physics |volume=92 |issue=2 |page=025002{{hyphen}}3 |doi=10.1103/RevModPhys.92.025002|arxiv=1903.09051 |bibcode=2020RvMP...92b5002X |s2cid=210942877 }}</ref> With appropriate cryptographic protocols, the sender and receiver can thus establish shared private information resistant to eavesdropping.<ref name="bb84" /><ref>{{Cite conference |last1=Xu |first1=Guobin |last2=Mao |first2=Jianzhou |last3=Sakk |first3=Eric |last4=Wang |first4=Shuangbao Paul |title=2023 57th Annual Conference on Information Sciences and Systems (CISS) |date=2023-03-22 |chapter=An Overview of Quantum-Safe Approaches: Quantum Key Distribution and Post-Quantum Cryptography |publisher=IEEE |page=3 |doi=10.1109/CISS56502.2023.10089619 |isbn=978-1-6654-5181-9}}</ref>

Modern fiber-optic cables can transmit quantum information over relatively short distances. Ongoing experimental research aims to develop more reliable hardware (such as quantum repeaters), hoping to scale this technology to long-distance quantum networks with end-to-end entanglement. Theoretically, this could enable novel technological applications, such as distributed quantum computing and enhanced quantum sensing.<ref>{{Cite conference |last1=Kozlowski |first1=Wojciech |last2=Wehner |first2=Stephanie |title=Proceedings of the Sixth Annual ACM International Conference on Nanoscale Computing and Communication |date=2019-09-25 |chapter=Towards Large-Scale Quantum Networks |pages=1–7 |language=en |publisher=ACM |doi=10.1145/3345312.3345497 |isbn=978-1-4503-6897-1|arxiv=1909.08396 }}</ref><ref>{{Cite journal |last1=Guo |first1=Xueshi |last2=Breum |first2=Casper R. |last3=Borregaard |first3=Johannes |last4=Izumi |first4=Shuro |last5=Larsen |first5=Mikkel V. |last6=Gehring |first6=Tobias |last7=Christandl |first7=Matthias |last8=Neergaard-Nielsen |first8=Jonas S. |last9=Andersen |first9=Ulrik L. |date=23 December 2019 |title=Distributed quantum sensing in a continuous-variable entangled network |journal=Nature Physics |language=en |volume=16 |issue=3 |pages=281–284 |doi=10.1038/s41567-019-0743-x |arxiv=1905.09408 |s2cid=256703226 |issn=1745-2473}}</ref>

== Algorithms ==

<!-- Overview of quantum algorithms, particularly abstract routines with no explicit application -->
Progress in finding quantum algorithms typically focuses on the quantum circuit model,<ref name="quantum circuits"/> though exceptions like the [[Physics:Adiabatic quantum computation|quantum adiabatic algorithm]] exist. Quantum algorithms can be roughly categorized by the type of speedup achieved over corresponding classical algorithms.<ref name="zoo">{{cite web |author=Jordan |first=Stephen |date=14 October 2022 |title=Quantum Algorithm Zoo |url=http://math.nist.gov/quantum/zoo/ |url-status=live |archive-url=https://web.archive.org/web/20180429014516/https://math.nist.gov/quantum/zoo/ |archive-date=29 April 2018 |orig-date=22 April 2011}}</ref>

Quantum algorithms that offer more than a polynomial speedup over the best-known classical algorithm include [[Shor's algorithm]] for factoring and the related quantum algorithms for computing [[Discrete logarithm|discrete logarithm]]s, solving [[Pell's equation]], and, more generally, solving the [[Hidden subgroup problem|hidden subgroup problem]] for [[Abelian group|abelian]] finite groups.<ref name="zoo"/> These algorithms depend on the primitive of the [[Quantum Fourier transform|quantum Fourier transform]]. No mathematical proof has been found that shows that an equally fast classical algorithm cannot be discovered, but evidence suggests that this is unlikely.<ref>{{Cite conference |last1=Aaronson |first1=Scott |last2=Arkhipov |first2=Alex |date=2011-06-06 |title=The computational complexity of linear optics |book-title=Proceedings of the forty-third annual ACM symposium on Theory of computing |language=en |location=San Jose, California |publisher=[[Organization:Association for Computing Machinery|Association for Computing Machinery]] |pages=333–342 |doi=10.1145/1993636.1993682 |isbn=978-1-4503-0691-1 |arxiv=1011.3245}}</ref> Certain oracle problems like [[Simon's problem]] and the [[Bernstein–Vazirani algorithm|Bernstein–Vazirani problem]] do give provable speedups, though this is in the [[Quantum complexity theory#Quantum query complexity|quantum query model]], which is a restricted model where lower bounds are much easier to prove and don't necessarily translate to speedups for practical problems.

Other problems, including the simulation of quantum physical processes from chemistry and solid-state physics, the approximation of certain [[Jones polynomial]]s, and the [[Quantum algorithm for linear systems of equations|quantum algorithm for linear systems of equations]], have quantum algorithms appearing to give super-polynomial speedups and are [[BQP]]-complete. Because these problems are BQP-complete, an equally fast classical algorithm for them would imply that "no quantum algorithm" provides a super-polynomial speedup, which is believed to be unlikely.{{sfn|Nielsen|Chuang|2010|p=42}}

In addition to these problems, quantum algorithms are being explored for applications in cryptography, optimization, and machine learning, although most of these remain at the research stage and require significant advances in error correction and hardware scalability before practical implementation.{{sfn|Preskill|2018}}

Some quantum algorithms, such as [[Grover's algorithm]] and [[Amplitude amplification|amplitude amplification]], give polynomial speedups over corresponding classical algorithms.<ref name="zoo"/> Though these algorithms give comparably modest quadratic speedup, they are widely applicable and thus give speedups for a wide range of problems.{{sfn|Nielsen|Chuang|2010|p=7}} These speed-ups are, however, over the theoretical worst-case of classical algorithms, and concrete real-world speed-ups over algorithms used in practice have not been demonstrated.

=== Simulation of quantum systems ===

Since chemistry and nanotechnology rely on understanding quantum systems, and such systems are impossible to simulate in an efficient manner classically, [[Quantum simulator|quantum simulation]] may be an important application of quantum computing.<ref>{{Cite magazine |url=http://archive.wired.com/science/discoveries/news/2007/02/72734 |title=The Father of Quantum Computing |magazine=Wired |first=Quinn |last=Norton |date=15 February 2007 }}</ref> Quantum simulation could also be used to simulate the behavior of atoms and particles at unusual conditions such as the reactions inside a [[Physics:Collider|collider]].<ref>{{cite web |url=http://www.ias.edu/ias-letter/ambainis-quantum-computing |title=What Can We Do with a Quantum Computer? |first=Andris |last=Ambainis |date=Spring 2014 |publisher=Institute for Advanced Study}}</ref> In June 2023, IBM computer scientists reported that a quantum computer produced better results for a physics problem than a conventional supercomputer.<ref name="NYT-20230614">{{cite news |last=Chang |first=Kenneth |date=14 June 2023 |title=Quantum Computing Advance Begins New Era, IBM Says – A quantum computer came up with better answers to a physics problem than a conventional supercomputer. |work=The New York Times |url=https://www.nytimes.com/2023/06/14/science/ibm-quantum-computing.html |url-status=live |access-date=15 June 2023 |archive-url=https://archive.today/20230614151835/https://www.nytimes.com/2023/06/14/science/ibm-quantum-computing.html |archive-date=14 June 2023}}</ref><ref name="NAT-20230614">{{cite journal |author=Kim, Youngseok |display-authors=et al. |title=Evidence for the utility of quantum computing before fault tolerance |date=14 June 2023 |journal=Nature |volume=618 |issue=7965 |pages=500–505 |doi=10.1038/s41586-023-06096-3 |pmid=37316724 |pmc=10266970 |bibcode=2023Natur.618..500K }}</ref>

About 2% of the annual global energy output is used for [[Biology:Nitrogen fixation|nitrogen fixation]] to produce [[Chemistry:Ammonia|ammonia]] for the [[Chemistry:Haber process|Haber process]] in the agricultural fertiliser industry (even though naturally occurring organisms also produce ammonia). Quantum simulations might be used to understand this process and increase the energy efficiency of production.<ref>{{Cite AV media |url=https://www.youtube.com/watch?v=7susESgnDv8 |archive-url=https://web.archive.org/web/20210215140237/https://www.youtube.com/watch?v=7susESgnDv8 |archive-date=15 February 2021 |url-status=bot: unknown |title=Lunch & Learn: Quantum Computing |publisher=[[Finance:Sibos (conference)|Sibos TV]] |via=YouTube |date=21 November 2018 |access-date=4 February 2021 |first=Andrea |last=Morello |author-link=Andrea Morello }}</ref> It is expected that an early use of quantum computing will be modeling that improves the efficiency of the Haber–Bosch process<ref>{{Cite news |last1=Ruane |first1=Jonathan |last2=McAfee |first2=Andrew |last3=Oliver |first3=William D. |date=2022-01-01 |title=Quantum Computing for Business Leaders |work=Harvard Business Review |url=https://hbr.org/2022/01/quantum-computing-for-business-leaders |access-date=2023-04-12 |issn=0017-8012}}</ref> by the mid-2020s<ref>{{Cite web |last1=Budde |first1=Florian |last2=Volz |first2=Daniel |date=July 12, 2019 |title=Quantum computing and the chemical industry {{!}} McKinsey |url=https://www.mckinsey.com/industries/chemicals/our-insights/the-next-big-thing-quantum-computings-potential-impact-on-chemicals |access-date=2023-04-12 |website=www.mckinsey.com |publisher=McKinsey and Company }} </ref> although some have predicted it will take longer.<ref>{{Cite web |last=Bourzac |first=Katherine |date=October 30, 2017 |title=Chemistry is quantum computing's killer app |url=https://cen.acs.org/articles/95/i43/Chemistry-quantum-computings-killer-app.html |access-date=2023-04-12 |website=cen.acs.org |publisher=American Chemical Society}}</ref>

=== Post-quantum cryptography ===
{{Main|Post-quantum cryptography}}

A notable application of quantum computing is in [[Cryptanalysis|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 [[Computer|classical computer]] for large integers if they are the product of a few [[Prime number|prime number]]s (e.g., the product of two 300-digit primes).<ref>{{cite journal |last=Lenstra |first=Arjen K. |url=http://sage.math.washington.edu/edu/124/misc/arjen_lenstra_factoring.pdf |title=Integer Factoring |journal=Designs, Codes and Cryptography |volume=19 |pages=101–128 |year=2000 |doi=10.1023/A:1008397921377 |issue=2/3 |s2cid=9816153 |archive-url=https://web.archive.org/web/20150410234239/http://sage.math.washington.edu/edu/124/misc/arjen_lenstra_factoring.pdf |archive-date=10 April 2015 }}</ref> By contrast, a quantum computer could solve this problem exponentially faster using Shor's algorithm to factor the integer.{{sfn|Nielsen|Chuang|2010|p=216}} This ability would allow a quantum computer to break many of the [[Cryptography|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|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 topic under the field of ''post-quantum cryptography''.<ref name="pqcrypto_survey">{{cite book |doi=10.1007/978-3-540-88702-7_1 |chapter=Introduction to post-quantum cryptography |title=Post-Quantum Cryptography |year=2009 |last1=Bernstein |first1=Daniel J. |pages=1–14 |isbn=978-3-540-88701-0 |place=Berlin, Heidelberg |publisher=Springer|s2cid=61401925 }}</ref><ref>See also [http://pqcrypto.org/ pqcrypto.org], a bibliography maintained by Daniel J. Bernstein and [[Biography:Tanja Lange|Tanja Lange]] on cryptography not known to be broken by quantum computing.</ref> Some public-key algorithms are based on problems other than the integer factorization and discrete logarithm problems to which Shor's algorithm applies, such as the [[McEliece cryptosystem]], which relies on a hard problem in [[Coding theory|coding theory]].<ref name="pqcrypto_survey" /><ref>{{cite journal |last1=McEliece |first1=R. J. |title=A Public-Key Cryptosystem Based On Algebraic Coding Theory |journal=DSNPR |date=January 1978 |volume=44 |pages=114–116 |url=http://ipnpr.jpl.nasa.gov/progress_report2/42-44/44N.PDF |bibcode=1978DSNPR..44..114M}}</ref> [[Lattice-based cryptography|Lattice-based cryptosystems]] are also not known to be broken by quantum computers, and finding a polynomial time algorithm for solving the [[Dihedral group|dihedral]] [[Hidden subgroup problem|hidden subgroup problem]], which would break many lattice-based cryptosystems, is a well-studied open problem.<ref>{{cite journal |last1=Kobayashi |first1=H. |last2=Gall |first2=F. L. |year=2006 |title=Dihedral Hidden Subgroup Problem: A Survey |journal=Information and Media Technologies |volume=1 |issue=1 |pages=178–185 |doi=10.2197/ipsjdc.1.470 |doi-access=free}}</ref> It has been shown that applying Grover's algorithm to break a [[Symmetric-key algorithm|symmetric (secret-key) algorithm]] by brute force requires time equal to roughly 2<sup>''n''/2</sup> invocations of the underlying cryptographic algorithm, compared with roughly 2<sup>''n''</sup> in the classical case,<ref name=bennett_1997>{{cite journal |last1=Bennett |first1=Charles H. |last2=Bernstein |first2=Ethan |last3=Brassard |first3=Gilles |last4=Vazirani |first4=Umesh |title=Strengths and Weaknesses of Quantum Computing |journal=SIAM Journal on Computing |date=October 1997 |volume=26 |issue=5 |pages=1510–1523 |doi=10.1137/s0097539796300933 |arxiv=quant-ph/9701001 |bibcode=1997quant.ph..1001B |s2cid=13403194 }}</ref> meaning that symmetric key lengths are effectively halved: AES-256 would have comparable security against an attack using Grover's algorithm to that AES-128 has against classical brute-force search (see ''[[Social:Key size#Effect of quantum computing attacks on key strength|Key size]]'').

=== Search problems<span class="anchor" id="Quantum search"></span> ===
{{Main|Grover's algorithm}}

The most well-known example of a problem that allows for a polynomial quantum speedup is ''unstructured search'', which involves finding a marked item out of a list of <math>n</math> items in a database. This can be solved by Grover's algorithm using <math>O(\sqrt{n})</math> queries to the database, quadratically fewer than the <math>\Omega(n)</math> queries required for classical algorithms. In this case, the advantage is not only provable but also optimal: it has been shown that Grover's algorithm gives the maximal possible probability of finding the desired element for any number of oracle lookups. Many examples of provable quantum speedups for query problems are based on Grover's algorithm, including [[BHT algorithm|Brassard, Høyer, and Tapp's algorithm]] for finding collisions in two-to-one functions,<ref>{{cite encyclopedia |year=2016 |chapter=Quantum Algorithm for the Collision Problem |encyclopedia=Encyclopedia of Algorithms |publisher=Springer |place=New York, New York |editor-last=Kao |editor-first=Ming-Yang |pages=1662–1664 |language=en |arxiv=quant-ph/9705002 |doi=10.1007/978-1-4939-2864-4_304 |isbn=978-1-4939-2864-4 |last2=Høyer |first2=Peter |last3=Tapp |first3=Alain |last1=Brassard |first1=Gilles |s2cid=3116149}}</ref> and Farhi, Goldstone, and Gutmann's algorithm for evaluating NAND trees.<ref>{{Cite journal |last1=Farhi |first1=Edward |last2=Goldstone |first2=Jeffrey |last3=Gutmann |first3=Sam |date=23 December 2008 |title=A Quantum Algorithm for the Hamiltonian NAND Tree |journal=Theory of Computing |language=EN |volume=4 |issue=1 |pages=169–190 |doi=10.4086/toc.2008.v004a008 |s2cid=8258191 |issn=1557-2862 |doi-access=free}}</ref>

Problems that can be efficiently addressed with Grover's algorithm have the following properties:<ref>{{cite book |author=Williams |first=Colin P. |title=Explorations in Quantum Computing |publisher=[[Company:Springer Science+Business Media|Springer]] |year=2011 |isbn=978-1-84628-887-6 |pages=242–244}}</ref><ref>{{cite arXiv |last=Grover| first=Lov| title=A fast quantum mechanical algorithm for database search |date=29 May 1996| eprint=quant-ph/9605043}}</ref>
#There is no searchable structure in the collection of possible answers,
#The number of possible answers to check is the same as the number of inputs to the algorithm, and
#There exists a Boolean function that evaluates each input and determines whether it is the correct answer.

For problems with all these properties, the running time of Grover's algorithm on a quantum computer scales as the square root of the number of inputs (or elements in the database), as opposed to the linear scaling of classical algorithms. A general class of problems to which Grover's algorithm can be applied<ref>{{cite journal |last1=Ambainis |first1=Ambainis |title=Quantum search algorithms |journal=ACM SIGACT News |date=June 2004 |volume=35 |issue=2 |pages=22–35 |doi=10.1145/992287.992296 |arxiv=quant-ph/0504012 |bibcode=2005quant.ph..4012A |s2cid=11326499 }}</ref> is a [[Boolean satisfiability problem]], where the ''database'' through which the algorithm iterates is that of all possible answers. An example and possible application of this is a [[Password cracking|password cracker]] that attempts to guess a password. Breaking [[Symmetric-key algorithm|symmetric ciphers]] with this algorithm is of interest to government agencies.<ref>{{cite news |url=https://www.washingtonpost.com/world/national-security/nsa-seeks-to-build-quantum-computer-that-could-crack-most-types-of-encryption/2014/01/02/8fff297e-7195-11e3-8def-a33011492df2_story.html |title=NSA seeks to build quantum computer that could crack most types of encryption |first1=Steven |last1=Rich |first2=Barton |last2=Gellman |date=1 February 2014 |newspaper=The Washington Post}}</ref>

=== Quantum annealing<span class="anchor" id="Quantum annealing and adiabatic optimization"></span> ===

[[Quantum annealing]] relies on the adiabatic theorem to undertake calculations. A system is placed in the ground state for a simple Hamiltonian, which slowly evolves to a more complicated Hamiltonian whose ground state represents the solution to the problem in question. The adiabatic theorem states that if the evolution is slow enough, the system will stay in its ground state at all times through the process. Quantum annealing can solve [[Ising model]]s and the (computationally equivalent) QUBO problem, which in turn can be used to encode a wide range of [[Combinatorial optimization|combinatorial optimization]] problems.<ref>{{Cite journal |last1=Lucas |first1=Andrew |date=2014 |title=Ising formulations of many NP problems |journal=Frontiers in Physics |volume=2 |page=5|doi=10.3389/fphy.2014.00005 |doi-access=free |arxiv=1302.5843 |bibcode=2014FrP.....2....5L }}</ref> {{anchor|Computational biology}}Adiabatic optimization may be helpful for solving [[Biology:Computational biology|computational biology]] problems.<ref>{{cite journal |last1=Outeiral |first1=Carlos| last2=Strahm |first2=Martin |last3=Morris |first3=Garrett |last4=Benjamin |first4=Simon |last5=Deane |first5=Charlotte |last6=Shi |first6=Jiye |title=The prospects of quantum computing in computational molecular biology |journal=WIREs Computational Molecular Science |year=2021|volume=11|article-number=e1481 |doi=10.1002/wcms.1481 |arxiv=2005.12792 |s2cid=218889377 |doi-access=free}}</ref>

=== Machine learning ===
{{Main|Quantum machine learning}}

Since quantum computers can produce outputs that classical computers cannot produce efficiently, and since quantum computation is fundamentally linear algebraic, some express hope in developing quantum algorithms that can speed up [[Machine learning|machine learning]] tasks.<ref name="preskill2018"/><ref>{{Cite journal |last1=Biamonte |first1=Jacob |last2=Wittek |first2=Peter |last3=Pancotti |first3=Nicola |last4=Rebentrost |first4=Patrick |last5=Wiebe |first5=Nathan |last6=Lloyd |first6=Seth |date=September 2017 |title=Quantum machine learning |journal=Nature |language=en |volume=549 |issue=7671 |pages=195–202 |doi=10.1038/nature23474 |pmid=28905917 |arxiv=1611.09347 |bibcode=2017Natur.549..195B |s2cid=64536201 |issn=0028-0836}}</ref>

For example, the HHL Algorithm, named after its discoverers Harrow, Hassidim, and Lloyd, is believed to provide speedup over classical counterparts.<ref name="preskill2018"/><ref name="Quantum algorithm for solving linear systems of equations by Harrow et al.">{{Cite journal |arxiv=0811.3171 |last1=Harrow |first1=Aram |last2=Hassidim |first2=Avinatan |last3=Lloyd |first3=Seth |title=Quantum algorithm for solving linear systems of equations |journal=Physical Review Letters |volume=103 |issue=15 |article-number=150502 |year=2009 |doi=10.1103/PhysRevLett.103.150502 |pmid=19905613 |bibcode=2009PhRvL.103o0502H |s2cid=5187993}}</ref> Some research groups have recently explored the use of quantum annealing hardware for training [[Boltzmann machine]]s and deep neural networks.<ref>{{Cite journal |last1=Benedetti |first1=Marcello |last2=Realpe-Gómez |first2=John |last3=Biswas |first3=Rupak |last4=Perdomo-Ortiz |first4=Alejandro |date=9 August 2016 |title=Estimation of effective temperatures in quantum annealers for sampling applications: A case study with possible applications in deep learning |journal=Physical Review A |volume=94 |issue=2 |article-number=022308 |doi=10.1103/PhysRevA.94.022308 |arxiv=1510.07611 |bibcode=2016PhRvA..94b2308B |doi-access=free}}</ref><ref>{{Cite journal |last1=Ajagekar |first1=Akshay |last2=You |first2=Fengqi |date=5 December 2020 |title=Quantum computing assisted deep learning for fault detection and diagnosis in industrial process systems |journal=Computers & Chemical Engineering |language=en |volume=143 |article-number=107119 |arxiv=2003.00264 |s2cid=211678230 |doi=10.1016/j.compchemeng.2020.107119 |issn=0098-1354}}</ref><ref>{{Cite journal |last1=Ajagekar |first1=Akshay |last2=You |first2=Fengqi |date=2021-12-01 |title=Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems |journal=Applied Energy |language=en |volume=303 |article-number=117628 |doi=10.1016/j.apenergy.2021.117628 |issn=0306-2619 |doi-access=free|bibcode=2021ApEn..30317628A }}</ref>

{{anchor|Computer-aided drug design and generative chemistry}}
Deep generative chemistry models emerge as powerful tools to expedite [[Medicine:Drug discovery|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.<ref>{{cite journal |last1=Fedichev |first1=Peter |last2=Pyrkov |first2=Timothy |last3=Krylov |first3=Ivan |title=Quantum machine learning for drug discovery |journal=Scientific Reports |volume=13 |year=2023 |pages= |doi=10.1038/s41598-023-32703-4}}</ref><ref>{{cite news |last=Borfitz |first=Deborah |title=Gero Taps Quantum Computing and AI To Tackle Diseases Of Aging |url=https://www.bio-itworld.com/news/2023/08/22/gero-taps-quantum-computing-and-ai-to-tackle-diseases-of-aging |work=Bio-IT World |date=22 August 2023}}</ref> 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<ref name="273.5278.1073"/> and thus may be instrumental in applications involving quantum chemistry. Therefore, one can expect that quantum-enhanced generative models<ref>{{cite journal |last1=Gao |first1=Xun |last2=Anschuetz |first2=Eric R. |last3=Wang |first3=Sheng-Tao |last4=Cirac |first4=J. Ignacio |last5=Lukin |first5=Mikhail D. |title=Enhancing Generative Models via Quantum Correlations |journal=Physical Review X |year=2022 |volume=12 |issue=2 |article-number=021037 |doi=10.1103/PhysRevX.12.021037 |arxiv=2101.08354 |bibcode=2022PhRvX..12b1037G |s2cid=231662294}}</ref> including quantum GANs<ref>{{cite journal |last1=Li |first1=Junde |last2=Topaloglu |first2=Rasit |last3=Ghosh |first3=Swaroop |title=Quantum Generative Models for Small Molecule Drug Discovery |journal=IEEE Transactions on Quantum Engineering |date=9 January 2021 |volume=2 |pages=1–8 |doi=10.1109/TQE.2021.3104804 |arxiv=2101.03438 |bibcode=2021ITQE....2E4804L }}</ref> may eventually be developed into ultimate generative chemistry algorithms.

== Engineering<span class="anchor" id="Developing physical quantum computers"></span> ==
[[File:A Wafer of the Latest D-Wave Quantum Computers (39188583425).jpg|thumb|A [[wafer (electronics)|wafer]] of adiabatic quantum computers]]
{{As of|2023|post=,}} 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.<ref name="good-for-nothing" /><ref name="CACM" />

=== Challenges ===

There are a number of technical challenges in building a large-scale quantum computer.<ref>{{cite journal |last=Dyakonov |first=Mikhail |url=https://spectrum.ieee.org/the-case-against-quantum-computing |title=The Case Against Quantum Computing |journal=IEEE Spectrum |date=15 November 2018}}</ref> Physicist David DiVincenzo has listed [[DiVincenzo's criteria|these requirements]] for a practical quantum computer:<ref>{{cite journal| arxiv=quant-ph/0002077 |title=The Physical Implementation of Quantum Computation |last=DiVincenzo |first=David P. |date=13 April 2000 |doi=10.1002/1521-3978(200009)48:9/11<771::AID-PROP771>3.0.CO;2-E |volume=48 |issue=9–11 |journal=Fortschritte der Physik |pages=771–783 |bibcode=2000ForPh..48..771D |s2cid=15439711}}</ref>
* Physically scalable to increase the number of qubits
* Qubits that can be initialized to arbitrary values
* Quantum gates that are faster than [[Physics:Decoherence|decoherence]] time
* Universal gate set
* Qubits that can be read easily.

Sourcing parts for quantum computers is also very difficult. [[Superconducting quantum computing|Superconducting quantum computers]], like those constructed by [[Company:Google|Google]] and [[Company:IBM|IBM]], need [[Physics:Helium-3|helium-3]], a [[Physics:Nuclear physics|nuclear]] research byproduct, and special [[Physics:Superconducting|superconducting]] cables made only by the Japanese company Coax Co.<ref>{{cite news |last1=Giles |first1=Martin |date=January 17, 2019 |title=We'd have more quantum computers if it weren't so hard to find the damn cables |language=en-US |publisher=MIT Technology Review |url=https://www.technologyreview.com/s/612760/quantum-computers-component-shortage/ |access-date=May 17, 2021}}</ref>

The control of multi-qubit systems requires the generation and coordination of a large number of electrical signals with tight and deterministic timing resolution. This has led to the development of quantum controllers that enable interfacing with the qubits. Scaling these systems to support a growing number of qubits is an additional challenge.<ref>{{cite journal |vauthors=Pauka SJ, Das K, Kalra B, Moini A, Yang Y, Trainer M, Bousquet A, Cantaloube C, Dick N, Gardner GC, Manfra MJ, Reilly DJ|journal=[[Engineering:Nature Electronics|Nature Electronics]]|title=A cryogenic CMOS chip for generating control signals for multiple qubits|year=2021|volume=4|issue=4|pages=64–70 |doi=10.1038/s41928-020-00528-y|url=https://www.nature.com/articles/s41928-020-00528-y|arxiv=1912.01299|s2cid=231715555}}</ref>

==== Decoherence<span class="anchor" id="Quantum decoherence"></span> ====

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 ''T''<sub>2</sub> (for [[Physics:Nuclear magnetic resonance|NMR]] and MRI technology, also called the ''dephasing time''), typically range between nanoseconds and seconds at low temperatures.<ref name="DiVincenzo 1995">{{cite journal |last=DiVincenzo |first=David P. |title=Quantum Computation |journal=Science |year=1995 |volume=270 |issue=5234 |pages=255–261 |doi=10.1126/science.270.5234.255 |bibcode=1995Sci...270..255D |citeseerx=10.1.1.242.2165 |s2cid=220110562}}</ref> Currently, some quantum computers require their qubits to be cooled to 20 millikelvin (usually using a [[Physics:Dilution refrigerator|dilution refrigerator]]<ref>{{Cite journal |doi=10.1016/j.cryogenics.2021.103390| issn=0011-2275 |title=Development of Dilution refrigerators – A review |journal=Cryogenics| volume=121| year=2022| last1=Zu| first1=H.| last2=Dai| first2=W.| last3=de Waele| first3=A.T.A.M.| s2cid=244005391}}</ref>) in order to prevent significant decoherence.<ref>{{cite journal |last1=Jones |first1=Nicola |title=Computing: The quantum company |journal=Nature |date=19 June 2013 |volume=498 |issue=7454 |pages=286–288 |doi=10.1038/498286a|pmid=23783610|bibcode=2013Natur.498..286J|doi-access=free}}</ref> A 2020 study argues that [[Physics:Ionizing radiation|ionizing radiation]] such as cosmic rays can nevertheless cause certain systems to decohere within milliseconds.<ref>{{cite journal |last1=Vepsäläinen |first1=Antti P. |last2=Karamlou |first2=Amir H. |last3=Orrell |first3=John L. |last4=Dogra |first4=Akshunna S. |last5=Loer |first5=Ben |last6=Vasconcelos |first6=Francisca |last7=Kim |first7=David K. |last8=Melville |first8=Alexander J. |last9=Niedzielski |first9=Bethany M. |last10=Yoder |first10=Jonilyn L. |last11=Gustavsson |first11=Simon |last12=Formaggio |first12=Joseph A. |last13=VanDevender |first13=Brent A. |last14=Oliver |first14=William D. |display-authors=5 |title=Impact of ionizing radiation on superconducting qubit coherence |journal=Nature |date=August 2020 |volume=584 |issue=7822 |pages=551–556 |doi=10.1038/s41586-020-2619-8 |pmid=32848227 |url=https://www.nature.com/articles/s41586-020-2619-8 |language=en |issn=1476-4687|arxiv=2001.09190 |bibcode=2020Natur.584..551V |s2cid=210920566 }}</ref>

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.<ref>{{cite arXiv |last1=Amy |first1=Matthew |last2=Matteo |first2=Olivia |last3=Gheorghiu |first3=Vlad |last4=Mosca |first4=Michele |last5=Parent |first5=Alex |last6=Schanck |first6=John |title=Estimating the cost of generic quantum pre-image attacks on SHA-2 and SHA-3 |date=30 November 2016 |eprint=1603.09383 |class=quant-ph}}</ref>

These issues are more difficult for optical approaches as the timescales are orders of magnitude shorter, and an often-cited approach to overcoming them is optical [[Pulse shaping|pulse shaping]]. Error rates are typically proportional to the ratio of operating time to decoherence time; hence, any operation must be completed much more quickly than the decoherence time.

As described by the [[Threshold theorem|threshold theorem]], if the error rate is small enough, it is thought to be possible to use [[Quantum error correction|quantum error correction]] to suppress errors and decoherence. This allows the total calculation time to be longer than the decoherence time if the error correction scheme can correct errors faster than decoherence introduces them. An often-cited figure for the required error rate in each gate for fault-tolerant computation is 10<sup>−3</sup>, assuming the noise is depolarizing.

Meeting this scalability condition is possible for a wide range of systems. However, the use of error correction brings with it the cost of a greatly increased number of required qubits. The number required to factor integers using Shor's algorithm is still polynomial, and thought to be between ''L'' and ''L''<sup>2</sup>, where ''L'' is the number of binary digits in the number to be factored; error correction algorithms would inflate this figure by an additional factor of ''L''. For a 1000-bit number, this implies a need for about 10<sup>4</sup> bits without error correction.<ref>{{cite journal |last=Dyakonov |first=M. I. |date=14 October 2006 |editor2=Xu |editor2-first=J. |editor3=Zaslavsky |editor3-first=A. |title=Is Fault-Tolerant Quantum Computation Really Possible? |journal=Future Trends in Microelectronics. Up the Nano Creek |pages=4–18 |arxiv=quant-ph/0610117 |bibcode=2006quant.ph.10117D |editor1=S. Luryi}}</ref> With error correction, the figure would rise to about 10<sup>7</sup> bits. Computation time is about ''L''<sup>2</sup> or about 10<sup>7</sup> steps and at 1{{nbsp}}MHz, about 10 seconds. However, the encoding and error-correction overheads increase the size of a real fault-tolerant quantum computer by several orders of magnitude. Careful estimates<ref name=":1">{{Cite book |last=Ahsan |first=Muhammad |title=Architecture Framework for Trapped-ion Quantum Computer based on Performance Simulation Tool |date=2015 |bibcode=2015PhDT........56A |language=en-US |oclc=923881411}}</ref><ref name=":2">{{Cite journal |last1=Ahsan |first1=Muhammad |last2=Meter |first2=Rodney Van |last3=Kim |first3=Jungsang |date=2016-12-28 |title=Designing a Million-Qubit Quantum Computer Using a Resource Performance Simulator |journal=ACM Journal on Emerging Technologies in Computing Systems |volume=12 |issue=4 |pages=39:1–39:25 |doi=10.1145/2830570 |s2cid=1258374 |issn=1550-4832|doi-access=free |arxiv=1512.00796 }}</ref> show that at least 3{{nbsp}}million physical qubits would factor 2,048-bit integer in 5 months on a fully error-corrected trapped-ion quantum computer. In terms of the number of physical qubits, to date, this remains the lowest estimate<ref>{{Cite journal |last1=Gidney |first1=Craig |last2=Ekerå |first2=Martin |date=2021-04-15 |title=How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits |journal=Quantum |volume=5 |article-number=433 |doi=10.22331/q-2021-04-15-433 |arxiv=1905.09749 |bibcode=2021Quant...5..433G |s2cid=162183806 |issn=2521-327X}}</ref> for practically useful integer factorization problem sizing 1,024-bit or larger. 

One approach to overcoming errors combines [[Low-density parity-check code|low-density parity-check code]] with [[Physics:Cat qubit quantum computer|cat qubits]] that have intrinsic bit-flip error suppression. Implementing 100 logical qubits with 768 cat qubits could reduce the error rate to one part in 10<sup>8</sup> per cycle per bit.<ref>{{Cite journal |last1=Ruiz |first1=Diego |last2=Guillaud |first2=Jérémie |last3=Leverrier |first3=Anthony |last4=Mirrahimi |first4=Mazyar |last5=Vuillot |first5=Christophe |date=2025-01-26 |title=LDPC-cat codes for low-overhead quantum computing in 2D |journal=Nature Communications |volume=16 |issue=1 |article-number=1040 |doi=10.1038/s41467-025-56298-8 |pmid=39863608 |pmc=11762751 |arxiv=2401.09541 |bibcode=2025NatCo..16.1040R |issn=2041-1723}}</ref>

Another approach to the stability-decoherence problem is to create a [[Topological quantum computer|topological quantum computer]] with [[Anyon|anyon]]s, quasi-particles used as threads, and relying on [[Braid theory|braid theory]] to form stable logic gates.<ref>{{cite journal
 | last4 = Wang | first4 = Zhenghan
 | arxiv = quant-ph/0101025
 | doi = 10.1090/S0273-0979-02-00964-3
 | issue = 1
 | journal = Bulletin of the American Mathematical Society
 | mr = 1943131
 | pages = 31–38
 | title = Topological quantum computation
 | volume = 40
 | year = 2003}}</ref><ref>{{cite journal |last=Monroe |first=Don |url=https://www.newscientist.com/channel/fundamentals/mg20026761.700-anyons-the-breakthrough-quantum-computing-needs.html |title=Anyons: The breakthrough quantum computing needs? |journal=New Scientist |date=1 October 2008}}</ref> Non-Abelian anyons can, in effect, remember how they have been manipulated, making them potentially useful in quantum computing.<ref name=":0">{{Cite journal |last=Cossins |first=Daniel |date=28 June 2025 |title=How to think about...Quasiparticles |journal=New Scientist |volume=266 |issue=3549 |page=34 |doi=10.1016/S0262-4079(25)01046-2 }}</ref> As of 2025, Microsoft and other organizations are investing in quasi-particle research.<ref name=":0" />

=== Quantum supremacy ===

Physicist [[Biography:John Preskill|John Preskill]] coined the term ''quantum supremacy'' to describe the engineering feat of demonstrating that a programmable quantum device can solve a problem beyond the capabilities of state-of-the-art classical computers.<ref>{{cite arXiv |last=Preskill |first=John |date=2012-03-26 |title=Quantum computing and the entanglement frontier |eprint=1203.5813 |class=quant-ph}}</ref><ref name="preskill2018" /><ref>{{Cite journal |title=Characterizing Quantum Supremacy in Near-Term Devices|journal=Nature Physics |volume=14 |issue=6 |pages=595–600 |first1=Sergio |last1=Boixo |first2=Sergei V. |last2=Isakov |first3=Vadim N. |last3=Smelyanskiy |first4=Ryan |last4=Babbush |first5=Nan |last5=Ding |first6=Zhang |last6=Jiang |first7=Michael J. |last7=Bremner |first8=John M. |last8=Martinis |first9=Hartmut |last9=Neven |display-authors=5 |year=2018 |arxiv=1608.00263 |doi=10.1038/s41567-018-0124-x |bibcode=2018NatPh..14..595B |s2cid=4167494}}</ref> The problem need not be useful, so some view the quantum supremacy test only as a potential future benchmark.<ref>{{cite web |first=Neil |last=Savage |date=5 July 2017 |url=https://www.scientificamerican.com/article/quantum-computers-compete-for-supremacy/ |title=Quantum Computers Compete for "Supremacy" |work=Scientific American}}</ref>

In October 2019, Google AI Quantum, with the help of NASA, became the first to claim to have achieved quantum supremacy by performing calculations on the [[Sycamore processor|Sycamore quantum computer]] more than 3,000,000 times faster than they could be done on Summit, generally considered the world's fastest computer.<ref name="1910.11333"/><ref>{{cite web |last=Giles |first=Martin |date=September 20, 2019 |title=Google researchers have reportedly achieved 'quantum supremacy' |website=MIT Technology Review |language=en |url=https://www.technologyreview.com/f/614416/google-researchers-have-reportedly-achieved-quantum-supremacy/ |access-date=May 15, 2020}}</ref><ref>{{Cite web |last=Tavares |first=Frank |date=2019-10-23 |title=Google and NASA Achieve Quantum Supremacy |url=http://www.nasa.gov/feature/ames/quantum-supremacy |access-date=2021-11-16 |website=NASA |language=en-US}}</ref> This claim has been subsequently challenged: IBM has stated that Summit can perform samples much faster than claimed,<ref>{{cite arXiv |last1=Pednault |first1=Edwin |last2=Gunnels |first2=John A. |last3=Nannicini |first3=Giacomo |last4=Horesh |first4=Lior |last5=Wisnieff |first5=Robert |date=2019-10-22|title=Leveraging Secondary Storage to Simulate Deep 54-qubit Sycamore Circuits |class=quant-ph |eprint=1910.09534}}</ref><ref>{{Cite journal |last=Cho |first=Adrian |date=2019-10-23 |title=IBM casts doubt on Google's claims of quantum supremacy |url=https://www.science.org/content/article/ibm-casts-doubt-googles-claims-quantum-supremacy |journal=Science |doi=10.1126/science.aaz6080 |s2cid=211982610 |issn=0036-8075}}</ref> and researchers have since developed better algorithms for the sampling problem used to claim quantum supremacy, giving substantial reductions to the gap between Sycamore and classical supercomputers<ref>{{Cite book |last1=Liu |first1=Yong (Alexander) |last2=Liu |first2=Xin (Lucy) |last3=Li |first3=Fang (Nancy) |last4=Fu |first4=Haohuan |last5=Yang |first5=Yuling |last6=Song |first6=Jiawei |last7=Zhao |first7=Pengpeng |last8=Wang |first8=Zhen |last9=Peng |first9=Dajia |last10=Chen |first10=Huarong |last11=Guo |first11=Chu |title=Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis |chapter=Closing the "quantum supremacy" gap |display-authors=5 |date=2021-11-14 |series=SC '21 |location=New York, New York |publisher=Association for Computing Machinery |pages=1–12 |arxiv=2110.14502 |doi=10.1145/3458817.3487399 |isbn=978-1-4503-8442-1 |s2cid=239036985}}</ref><ref>{{Cite journal |last1=Bulmer |first1=Jacob F. F. |last2=Bell |first2=Bryn A. |last3=Chadwick |first3=Rachel S. |last4=Jones |first4=Alex E. |last5=Moise |first5=Diana |last6=Rigazzi |first6=Alessandro |last7=Thorbecke |first7=Jan |last8=Haus |first8=Utz-Uwe |last9=Van Vaerenbergh |first9=Thomas |last10=Patel |first10=Raj B. |last11=Walmsley |first11=Ian A. |display-authors=5 |date=2022-01-28 |title=The boundary for quantum advantage in Gaussian boson sampling |journal=Science Advances |language=en |volume=8 |issue=4 |article-number=eabl9236 |doi=10.1126/sciadv.abl9236 |issn=2375-2548 |pmc=8791606 |pmid=35080972 |arxiv=2108.01622 |bibcode=2022SciA....8.9236B}}</ref><ref>{{Cite journal |last=McCormick |first=Katie |date=2022-02-10 |title=Race Not Over Between Classical and Quantum Computers |url=https://physics.aps.org/articles/v15/19 |journal=Physics |language=en |volume=15|article-number=19 |doi=10.1103/Physics.15.19 |bibcode=2022PhyOJ..15...19M |s2cid=246910085 |doi-access=free }}</ref> and even beating it.<ref>{{Cite journal |title=Solving the Sampling Problem of the Sycamore Quantum Circuits |journal=Physical Review Letters |arxiv=2111.03011 |last1=Pan |first1=Feng |last2=Chen |first2=Keyang |last3=Zhang |first3=Pan |year=2022 |volume=129 |issue=9 |article-number=090502 |doi=10.1103/PhysRevLett.129.090502 |pmid=36083655 |bibcode=2022PhRvL.129i0502P |s2cid=251755796}}</ref><ref>{{Cite journal |author=Cho |first=Adrian |date=2022-08-02 |title=Ordinary computers can beat Google's quantum computer after all |url=https://www.science.org/content/article/ordinary-computers-can-beat-google-s-quantum-computer-after-all |journal=Science |volume=377 |doi=10.1126/science.ade2364|url-access=subscription }}</ref><ref>{{Cite web |title=Google's 'quantum supremacy' usurped by researchers using ordinary supercomputer |url=https://techcrunch.com/2022/08/05/googles-quantum-supremacy-usurped-by-researchers-using-ordinary-supercomputer/ |access-date=2022-08-07 |website=TechCrunch |date=5 August 2022 |language=en-US}}</ref>

In December 2020, a group at USTC implemented a type of [[Boson sampling]] on 76 photons with a [[Linear optical quantum computing|photonic quantum computer]], [[Jiuzhang (quantum computer)|Jiuzhang]], to demonstrate quantum supremacy.<ref>{{Cite journal |last=Ball |first=Philip |date=2020-12-03 |title=Physicists in China challenge Google's 'quantum advantage' |journal=Nature |volume=588 |issue=7838 |page=380 |language=en |doi=10.1038/d41586-020-03434-7 |pmid=33273711 |bibcode=2020Natur.588..380B |s2cid=227282052 |doi-access=}}</ref><ref>{{Cite web |last=Garisto |first=Daniel |title=Light-based Quantum Computer Exceeds Fastest Classical Supercomputers |url=https://www.scientificamerican.com/article/light-based-quantum-computer-exceeds-fastest-classical-supercomputers/ |access-date=2020-12-07 |website=Scientific American |language=en}}</ref><ref>{{Cite web |last=Conover |first=Emily |date=2020-12-03 |title=The new light-based quantum computer Jiuzhang has achieved quantum supremacy |url=https://www.sciencenews.org/article/new-light-based-quantum-computer-jiuzhang-supremacy |access-date=2020-12-07 |website=Science News |language=en-US}}</ref> The authors claim that a classical contemporary supercomputer would require a computational time of 600 million years to generate the number of samples their quantum processor can generate in 20 seconds.<ref name=":6">{{Cite journal |last1=Zhong |first1=Han-Sen |last2=Wang |first2=Hui |last3=Deng |first3=Yu-Hao |last4=Chen |first4=Ming-Cheng |last5=Peng |first5=Li-Chao |last6=Luo |first6=Yi-Han |last7=Qin |first7=Jian |last8=Wu |first8=Dian |last9=Ding |first9=Xing |last10=Hu |first10=Yi |last11=Hu |first11=Peng |display-authors=5 |date=2020-12-03 |title=Quantum computational advantage using photons |journal=Science |volume=370 |issue=6523 |pages=1460–1463 |language=en |doi=10.1126/science.abe8770 |issn=0036-8075 |pmid=33273064 |arxiv=2012.01625 |bibcode=2020Sci...370.1460Z |s2cid=227254333}}</ref>

Claims of quantum supremacy have generated hype around quantum computing,<ref>{{Cite journal |last=Roberson |first=Tara M. |date=2020-05-21 |title=Can Hype Be a Force for Good? |journal=Public Understanding of Science |language=en |volume=29 |issue=5 |pages=544–552 |doi=10.1177/0963662520923109 |pmid=32438851 |s2cid=218831653 |issn=0963-6625|doi-access=free }}</ref> but they are based on contrived benchmark tasks that do not directly imply useful real-world applications.<ref name="good-for-nothing" /><ref>{{Cite journal |last1=Cavaliere |first1=Fabio |last2=Mattsson |first2=John |last3=Smeets |first3=Ben |date=September 2020 |title=The security implications of quantum cryptography and quantum computing |url=http://www.magonlinelibrary.com/doi/10.1016/S1353-4858%2820%2930105-7 |journal=Network Security |language=en |volume=2020 |issue=9 |pages=9–15 |doi=10.1016/S1353-4858(20)30105-7 |s2cid=222349414 |issn=1353-4858|url-access=subscription }}</ref>

In January 2024, a study published in ''Physical Review Letters'' provided direct verification of quantum supremacy experiments by computing exact amplitudes for experimentally generated bitstrings using a new-generation Sunway supercomputer, demonstrating a significant leap in simulation capability built on a multiple-amplitude tensor network contraction algorithm.<ref>{{Cite journal |last1=Liu |first1=Yong |last2=Chen |first2=Yaojian |last3=Guo |first3=Chu |last4=Song |first4=Jiawei |last5=Shi |first5=Xinmin |last6=Gan |first6=Lin |last7=Wu |first7=Wenzhao |last8=Wu |first8=Wei |last9=Fu |first9=Haohuan |last10=Liu |first10=Xin |last11=Chen |first11=Dexun |last12=Zhao |first12=Zhifeng |last13=Yang |first13=Guangwen |last14=Gao |first14=Jiangang |date=2024-01-16 |title=Verifying Quantum Advantage Experiments with Multiple Amplitude Tensor Network Contraction |url=https://link.aps.org/doi/10.1103/PhysRevLett.132.030601 |journal=Physical Review Letters |language=en |volume=132 |issue=3 |article-number=030601 |doi=10.1103/PhysRevLett.132.030601 |pmid=38307065 |issn=0031-9007|arxiv=2212.04749 |bibcode=2024PhRvL.132c0601L }}</ref>

=== 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".<ref name="good-for-nothing">
{{Cite journal| journal = Nature | title = Quantum computers: what are they good for? | date = 24 May 2023 | first = Michael | last = Brooks| volume = 617 | issue = 7962 | pages = S1–S3 | doi = 10.1038/d41586-023-01692-9 | pmid = 37225885 | bibcode = 2023Natur.617S...1B | s2cid = 258847001 | doi-access = free }}
</ref> 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<ref name = "CACM">{{Cite web | url = https://m-cacm.acm.org/magazines/2023/5/272276-disentangling-hype-from-practicality-on-realistically-achieving-quantum-advantage/fulltext | publisher = Communications of the ACM | date = May 2023 | title = Disentangling Hype from Practicality: On Realistically Achieving Quantum Advantage
|author1 = Torsten Hoefler | author2 =  Thomas Häner | author3 = Matthias Troyer}}
</ref> 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, but are still improving rapidly, particularly GPU accelerators.
* Current quantum computing hardware generates only a limited amount of [[Quantum entanglement|entanglement]] before getting overwhelmed by noise.
* Quantum algorithms provide speedup over conventional algorithms only for some tasks, and matching these tasks with practical applications proved challenging. Some promising tasks and applications require resources far beyond those available today.<ref>{{Cite web| url = https://m-cacm.acm.org/magazines/2022/12/266916-quantum-computers-and-the-universe/fulltext | publisher = Communications of the ACM
|title = Quantum Computers and the Universe | first = Don | last = Monroe | date = December 2022}}
</ref><ref>{{Cite web| url = https://thequantuminsider.com/2023/06/20/psiquantum-sees-700x-reduction-in-computational-resource-requirements-to-break-elliptic-curve-cryptography-with-a-fault-tolerant-quantum-computer/ | website = The Quanrum Insider | title = PsiQuantum Sees 700x Reduction in Computational Resource Requirements to Break Elliptic Curve Cryptography With a Fault Tolerant Quantum Computer| first = Matt | last = Swayne | date = June 20, 2023 }}
</ref> In particular, processing large amounts of non-quantum data is a challenge for quantum computers.<ref name=CACM/>
* Some promising algorithms have been "dequantized", i.e., their non-quantum analogues with similar complexity have been found.
* If [[Quantum error correction|quantum error correction]] is used to scale quantum computers to practical applications, its overhead may undermine the speedup offered by many quantum algorithms.<ref name=CACM/>
* Complexity analysis of algorithms sometimes makes abstract assumptions that do not hold in applications. For example, input data may not already be available encoded in quantum states, and "oracle functions" used in Grover's algorithm often have internal structure that can be exploited for faster algorithms.

In particular, building computers with large numbers of qubits may be futile if those qubits are not connected well enough and cannot maintain a sufficiently high degree of entanglement for a long time. When trying to outperform conventional computers, quantum computing researchers often look for new tasks that can be solved on quantum computers, but this leaves the possibility that efficient non-quantum techniques will be developed in response, as seen for Quantum supremacy demonstrations. Therefore, it is desirable to prove lower bounds on the complexity of best possible non-quantum algorithms (which may be unknown) and show that some quantum algorithms asymptotically improve upon those bounds.

Bill Unruh doubted the practicality of quantum computers in a paper published in 1994.<ref>{{Cite journal |last1=Unruh |first1=Bill |title=Maintaining coherence in Quantum Computers |journal=Physical Review A |volume=51 |issue=2 |pages=992–997 |arxiv=hep-th/9406058 |bibcode=1995PhRvA..51..992U |year=1995 |doi=10.1103/PhysRevA.51.992 |pmid=9911677 |s2cid=13980886}}</ref> [[Biography:Paul Davies|Paul Davies]] argued that a 400-qubit computer would even come into conflict with the cosmological information bound implied by the [[Physics:Holographic principle|holographic principle]].<ref>{{cite arXiv|last1=Davies|first1=Paul|date=6 March 2007 |title=The implications of a holographic universe for quantum information science and the nature of physical law |eprint=quant-ph/0703041}}</ref> Skeptics like [[Biography:Gil Kalai|Gil Kalai]] doubt that quantum supremacy will ever be achieved.<ref>{{cite web |author=Regan |first=K. W. |date=23 April 2016 |title=Quantum Supremacy and Complexity |url=https://rjlipton.wordpress.com/2016/04/22/quantum-supremacy-and-complexity/ |website=Gödel's Lost Letter and P=NP}}</ref><ref>{{cite journal |last1=Kalai |first1=Gil |date=May 2016 |title=The Quantum Computer Puzzle |journal=Notices of the AMS |volume=63 |number=5 |pages=508–516 |url=https://www.ams.org/journals/notices/201605/rnoti-p508.pdf}}</ref><ref>{{cite arXiv |last1=Rinott |first1=Yosef |last2=Shoham |first2=Tomer |last3=Kalai |first3=Gil |date=2021-07-13 |title=Statistical Aspects of the Quantum Supremacy Demonstration |class=quant-ph |eprint=2008.05177}}</ref> Physicist [[Biography:Mikhail Dyakonov|Mikhail Dyakonov]] has expressed skepticism of quantum computing as follows:
:"So the number of continuous parameters describing the state of such a useful quantum computer at any given moment must be... about 10<sup>300</sup>... Could we ever learn to control the more than 10<sup>300</sup> continuously variable parameters defining the quantum state of such a system? My answer is simple. ''No, never.''"<ref>{{cite web |last1=Dyakonov |first1=Mikhail |title=The Case Against Quantum Computing |url=https://spectrum.ieee.org/the-case-against-quantum-computing |website=IEEE Spectrum |date=15 November 2018 |access-date=3 December 2019}}</ref>

=== Physical realizations ===

[[File:IBM Q system (Fraunhofer 2).jpg|thumb|upright=1.2|[[IBM Q System One|Quantum System One]], a quantum computer by [[Company:IBM|IBM]] from 2019 with 20 superconducting qubits<ref>{{Cite news |last=Russell |first=John |date=January 10, 2019 |title=IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans |language=en-US |website=HPCwire |url=https://www.hpcwire.com/2019/01/10/ibm-quantum-update-q-system-one-launch-new-collaborators-and-qc-center-plans/ |access-date=2023-01-09}}</ref>]]

A practical quantum computer must use a physical system as a programmable quantum register.<ref>{{Cite journal |last1=Tacchino |first1=Francesco |last2=Chiesa |first2=Alessandro |last3=Carretta |first3=Stefano |last4=Gerace |first4=Dario |date=2019-12-19 |title=Quantum Computers as Universal Quantum Simulators: State-of-the-Art and Perspectives |url=https://onlinelibrary.wiley.com/doi/10.1002/qute.201900052 |journal=Advanced Quantum Technologies |language=en |volume=3 |issue=3 |article-number=1900052 |doi=10.1002/qute.201900052 |arxiv=1907.03505 |s2cid=195833616 |issn=2511-9044}}</ref> Researchers are exploring several technologies as candidates for reliable qubit implementations.{{sfn|Grumbling|Horowitz|2019|page=127}} [[Physics:Superconductors|Superconductors]] and trapped ions are some of the most developed proposals, but experimentalists are considering other hardware possibilities as well.{{sfn|Grumbling|Horowitz|2019|page=114}}
For example, [[Topological quantum computer|topological quantum computer]] approaches are being explored for more fault-tolerance computing systems.<ref>{{Cite journal |last1=Nayak |first1=Chetan |last2=Simon |first2=Steven H. |last3=Stern |first3=Ady |last4=Freedman |first4=Michael |last5=Das Sarma |first5=Sankar |date=2008-09-12 |title=Non-Abelian anyons and topological quantum computation |url=https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.80.1083 |journal=Reviews of Modern Physics |volume=80 |issue=3 |pages=1083–1159 |doi=10.1103/RevModPhys.80.1083|arxiv=0707.1889 |bibcode=2008RvMP...80.1083N }}</ref>

The first quantum logic gates were implemented with trapped ions and prototype general-purpose machines with up to 20 qubits have been realized. However, the technology behind these devices combines complex vacuum equipment, lasers, and microwave and radio frequency equipment, making full-scale processors difficult to integrate with standard computing equipment. Moreover, the trapped ion system itself has engineering challenges to overcome.{{sfn|Grumbling|Horowitz|2019|page=119}}

The largest commercial systems are based on [[Physics:Superconductor|superconductor]] devices and have scaled to 2000 qubits. However, the error rates for larger machines have been on the order of 5%. Technologically, these devices are all cryogenic and scaling to large numbers of qubits requires wafer-scale integration, a serious engineering challenge by itself.{{sfn|Grumbling|Horowitz|2019|page=126}}

In addition to cryogenic platforms, room-temperature approaches to spin–photon interfaces have been experimentally demonstrated. In 2025, researchers at Stanford University realized a nanoscale device in which a thin layer of molybdenum diselenide is integrated on a nanostructured silicon substrate, enabling a spin–photon interface that operates at ambient conditions using structured “twisted” light to couple electronic and photonic degrees of freedom.<ref name="Stanford2025">{{cite web
 | title = Scientists achieve breakthrough on quantum signaling
 | website = Stanford Report
 | publisher = Stanford University
 | date = 1 December 2025
 | url = https://news.stanford.edu/stories/2025/12/quantum-communication-room-temperature-breakthrough-research
 | access-date = 8 January 2026
}}</ref><ref name="Pan2025">{{cite journal
 | last1 = Pan
 | first1 = F.
 | last2 = Liu
 | first2 = F.
 | last3 = Heinz
 | first3 = T. F.
 | last4 = Dionne
 | first4 = J. A.
 | year = 2025
 | title = Room-temperature spin–photon interface in a molybdenum diselenide–silicon nanostructured device
 | journal = Nature Communications
}}</ref> Such room-temperature, chip-integrated spin–photon interfaces are being investigated as potential building blocks for heterogeneous quantum networks that combine different qubit modalities and reduce reliance on large cryogenic infrastructures.<ref name="Stanford2025" /><ref>{{cite web
 | title = Room-Temperature Device Advances Quantum Communication
 | website = Quantum Zeitgeist
 | date = 2 December 2025
 | url = https://quantumzeitgeist.com/quantum-communication-molybdenum-diselenide-quantum-device/
 | access-date = 8 January 2026
}}</ref>

== Potential applications ==

From the perspective of business management, the potential applications of quantum computing are commonly classified into four key domains: (1) cybersecurity; (2) data analytics and artificial intelligence; (3) optimization and simulation; and (4) data management and search.<ref>{{cite web |last1=Leong |first1=Kelvin |last2=Sung |first2=Anna |date= November 2022 |title= What Business Managers Should Know About Quantum Computing? |url=http://journalofinterdisciplinarysciences.com/wp-content/uploads/2022/10/3-What-Business-Managers-Should-Know-About-Quantum-Computing.pdf |access-date=13 August 2023 |website=Journal of Interdisciplinary Sciences |language=en-US}}</ref>

Other applications include healthcare (i.e., drug discovery), financial modeling, and natural language processing.<ref>{{Cite web |title=10 Quantum Computing Applications & Examples to Know |url=https://builtin.com/hardware/quantum-computing-applications |access-date=2025-06-21 |website=Built In |language=en}}</ref>

== Theory<span class="anchor" id="Relation to computability and complexity theory"></span> ==

=== Computability<span class="anchor" id="Computability theory"></span> ===

Any [[Computational problem|computational problem]] solvable by a classical computer is also solvable by a quantum computer.{{sfn|Nielsen|Chuang|2010|p=29}} Intuitively, this is because it is believed that all physical phenomena, including the operation of classical computers, can be described using [[Physics:Quantum mechanics|quantum mechanics]], which underlies the operation of quantum computers.

Conversely, any problem solvable by a quantum computer is also solvable by a classical computer. It is possible to simulate both quantum and classical computers manually with just some paper and a pen, if given enough time. More formally, any quantum computer can be simulated by a [[Turing machine]]. In other words, quantum computers provide no additional power over classical computers in terms of [[Computability|computability]]. This means that quantum computers cannot solve [[Undecidable problem|undecidable problem]]s like the [[Halting problem|halting problem]], and the existence of quantum computers does not disprove the [[Church–Turing thesis]].{{sfn|Nielsen|Chuang|2010|p=126}}

=== Complexity<span class="anchor" id="Quantum complexity theory"></span> ===
{{Main|Quantum complexity theory}}

<!-- Power and limits of quantum computers -->
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 [[Integer factorization|factor integers]], while this is not believed to be the case for classical computers.

<!-- Basic definition of BQP -->
The class of [[Computational problem|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 (complexity)|BPP]] ("bounded error, probabilistic, polynomial time"), the class of problems that can be solved by polynomial-time [[Probabilistic Turing machine|probabilistic Turing machine]]s with bounded error.{{sfn|Nielsen|Chuang|2010|p=41}} It is known that <math>\mathsf{BPP\subseteq BQP}</math> and is widely suspected that <math>\mathsf{BQP\subsetneq BPP}</math>, which intuitively would mean that quantum computers are more powerful than classical computers in terms of [[Time complexity|time complexity]].{{sfn|Nielsen|Chuang|2010|p=201}}

<!-- Relation of BQP to basic complexity classes -->
[[File:BQP complexity class diagram.svg|thumb|The suspected relationship of BQP to several classical complexity classes{{sfn|Nielsen|Chuang|2010|p=42}}]]
The exact relationship of BQP to [[P (complexity)|P]], [[NP (complexity)|NP]], and PSPACE is not known. However, it is known that <math>\mathsf{P\subseteq BQP \subseteq PSPACE}</math>; that is, all problems that can be efficiently solved by a deterministic classical computer can also be efficiently solved by a quantum computer, and all problems that can be efficiently solved by a quantum computer can also be solved by a deterministic classical computer with polynomial space resources. It is further suspected that BQP is a strict superset of P, meaning that there exist problems that are efficiently solvable by quantum computers that are not efficiently solvable by deterministic classical computers. For instance, integer factorization and the discrete logarithm problem are known to be in BQP and are suspected to be outside of P. On the relationship of BQP to NP, little is known beyond the fact that some NP problems that are believed not to be in P are also in BQP (integer factorization and the discrete logarithm problem are both in NP, for example). It is suspected that <math>\mathsf{NP\nsubseteq BQP}</math>; that is, it is believed that there are efficiently checkable problems that are not efficiently solvable by a quantum computer. As a direct consequence of this belief, it is also suspected that BQP is disjoint from the class of NP-complete problems (if an NP-complete problem were in BQP, then it would follow from NP-hardness that all problems in NP are in BQP).<ref name=BernVazi>{{cite journal |last1=Bernstein |first1=Ethan |last2=Vazirani |first2=Umesh |doi=10.1137/S0097539796300921 |title=Quantum Complexity Theory |year=1997 |pages=1411–1473 |volume=26 |journal=SIAM Journal on Computing |url=http://www.cs.berkeley.edu/~vazirani/bv.ps |issue=5|citeseerx=10.1.1.144.7852 }}</ref>

== See also ==
<!-- New links in alphabetical order please -->
{{cols|colwidth=21em}}
*{{annotated link|Company:D-Wave Systems}}
*{{annotated link|Engineering:Electronic quantum holography}}
*{{annotated link|Glossary of quantum computing}}
*{{annotated link|Intelligence Advanced Research Projects Activity}}
**{{annotated link|QpiAI-Indus}}
*{{annotated link|Company:IonQ}}
*{{annotated link|Social:List of emerging technologies}}
*[[List of quantum computing journals]]
*{{annotated link|List of quantum processors}}
*{{annotated link|Magic state distillation}}
*{{annotated link|Metacomputing}}
*{{annotated link|Natural computing}}
*{{annotated link|Non-local quantum computation}}
*{{annotated link|Optical computing}}
*{{annotated link|Quantum bus}}
*{{annotated link|Quantum cognition}}
*{{annotated link|Quantum sensor}}
*{{annotated link|Quantum volume}}
*{{annotated link|Physics:Quantum weirdness}}
*{{annotated link|Company:Rigetti Computing}}
*{{annotated link|Supercomputer}}
*{{annotated link|Theoretical computer science}}
*{{annotated link|Unconventional computing}}
*{{annotated link|Physics:Valleytronics}}
{{colend}}

== Notes ==
{{notelist}}

== References ==
{{Reflist|30em}}

==Sources==
* {{cite book |last=Aaronson |first=Scott |title=Quantum Computing Since Democritus |date=2013 |publisher=Cambridge University Press |isbn=978-0-521-19956-8 |oclc=829706638 |doi=10.1017/CBO9780511979309 }}
* {{cite book |doi=10.17226/25196 |title=Quantum Computing: Progress and Prospects |date=2019 |editor-first1=Emily |editor-last1=Grumbling |editor-first2=Mark |editor-last2=Horowitz |publisher=The National Academies Press |isbn=978-0-309-47970-7 |location=Washington, DC |s2cid=125635007 |oclc=1091904777}}
* {{cite book |last1=Mermin |first1=N. David |title=Quantum Computer Science: An Introduction |date=2007 |isbn=978-0-511-34258-5 |oclc=422727925 |doi=10.1017/CBO9780511813870 }}
* {{cite book |  last1=Nielsen |first1=Michael |last2=Chuang |first2=Isaac |title=[[Quantum Computation and Quantum Information]] |year=2010 |edition=10th anniversary |isbn=978-0-511-99277-3 |oclc= 700706156 |doi=10.1017/CBO9780511976667 | s2cid=59717455 }}
* {{Cite conference |last=Shor |first=Peter W. |date=1994 |title=Algorithms for Quantum Computation: Discrete Logarithms and Factoring |conference=Symposium on Foundations of Computer Science |location=Santa Fe, New Mexico |publisher=IEEE |pages=124{{en dash}}134 |doi=10.1109/SFCS.1994.365700 |isbn=978-0-8186-6580-6 |}}

== Further reading ==
{{refbegin|30em}}

===Textbooks===
* {{cite book |last1=Benenti |first1=Giuliano |last2=Casati |first2=Giulio |last3=Rossini |first3=Davide |last4=Strini |first4=Giuliano |title=Principles of Quantum Computation and Information: A Comprehensive Textbook |edition=2nd |year=2019 |isbn=978-981-3237-23-0 |oclc=1084428655 |doi=10.1142/10909 |s2cid=62280636 }}
* {{cite book |last=Bernhardt |first=Chris |year=2019 |title=Quantum Computing for Everyone |publisher=MIT Press |oclc=1082867954 |isbn=978-0-262-35091-4 }}
* {{cite book |editor-last1=Exman |editor-first1=Iaakov |editor-last2=Pérez-Castillo |editor-first2=Ricardo |editor-last3=Piattini |editor-first3=Mario |editor-last4=Felderer |editor-first4=Michael |title=Quantum Software: Aspects of Theory and System Design |year=2024 |url=https://link.springer.com/book/10.1007/978-3-031-64136-7 |isbn=978-3-031-64136-7 |publisher=[[Company:Springer Nature|Springer Nature]]|doi=10.1007/978-3-031-64136-7 }}
* {{cite book |last=Hidary |first=Jack D. |year=2021 |edition=2nd |title=Quantum Computing: An Applied Approach |oclc=1272953643 |isbn=978-3-03-083274-2 |doi=10.1007/978-3-030-83274-2 |s2cid=238223274 }}
* {{cite book |editor-last1=Hiroshi |editor-first1=Imai |editor-last2=Masahito |editor-first2=Hayashi |year=2006 |title = Quantum Computation and Information: From Theory to Experiment |series=Topics in Applied Physics |volume=102 |isbn=978-3-540-33133-9 |doi=10.1007/3-540-33133-6 }}
* {{cite book |last1=Hughes |first1=Ciaran |last2=Isaacson |first2=Joshua |last3=Perry |first3=Anastasia |last4=Sun |first4=Ranbel F. |last5=Turner |first5=Jessica |title=Quantum Computing for the Quantum Curious |isbn=978-3-03-061601-4 |oclc=1244536372 |doi=10.1007/978-3-030-61601-4 |year=2021 |s2cid=242566636 |url=https://link.springer.com/book/10.1007/978-3-030-61601-4 }}
* {{cite book |last=Jaeger |first=Gregg |title=Quantum Information: An Overview |year=2007 |isbn=978-0-387-36944-0 |oclc=186509710 |doi=10.1007/978-0-387-36944-0 }}
* {{cite book |last1=Johnston |first1=Eric R. |last2=Harrigan |first2=Nic |last3=Gimeno-Segovia |first3=Mercedes |title=Programming Quantum Computers: Essential Algorithms and Code Samples |year=2019 |publisher=O'Reilly Media, Incorporated |oclc=1111634190 |isbn=978-1-4920-3968-6 }}
* {{cite book |last1=Kaye |first1=Phillip |last2=Laflamme |first2=Raymond |last3=Mosca |first3=Michele |author-link3=Michele Mosca |title=An Introduction to Quantum Computing |year=2007 |publisher=OUP Oxford |oclc=85896383 |isbn=978-0-19-857000-4 }}
* {{cite book |last1=Kitaev |first1=Alexei Yu. |last2=Shen |first2=Alexander H. |last3=Vyalyi |first3=Mikhail N. |title=Classical and Quantum Computation |year=2002 |publisher=American Mathematical Soc. |oclc=907358694 |isbn=978-0-8218-3229-5 }}
* {{cite book |last1= Kurgalin|first1= Sergei|last2 = Borzunov|first2 = Sergei|date= 2021|title= Concise Guide to Quantum Computing: Algorithms, Exercises, and Implementations|publisher= Springer|doi= 10.1007/978-3-030-65052-0|isbn= 978-3-030-65052-0}}
* {{cite book |last1=Stolze |first1=Joachim |last2=Suter |first2=Dieter |year=2004 |title =Quantum Computing: A Short Course from Theory to Experiment |isbn =978-3-527-61776-0 |oclc=212140089 |doi=10.1002/9783527617760 }}
* {{Cite book |last1=Susskind |first1=Leonard |title=Quantum Mechanics: The Theoretical Minimum |last2=Friedman |first2=Art |date=2014 |publisher=Basic Books |isbn=978-0-465-08061-8 |location=New York |}}
* {{cite book |last=Wichert |first=Andreas |year=2020 |title=Principles of Quantum Artificial Intelligence: Quantum Problem Solving and Machine Learning |edition=2nd |doi=10.1142/11938 |isbn=978-981-12-2431-7 |s2cid=225498497 |oclc=1178715016 }}
* {{cite book |last=Wong |first=Thomas |title=Introduction to Classical and Quantum Computing |publisher=Rooted Grove |year=2022 |isbn=979-8-9855931-0-5 |oclc=1308951401 |url=http://www.thomaswong.net/introduction-to-classical-and-quantum-computing-1e.pdf |access-date=6 February 2022 |archive-date=29 January 2022 |archive-url=https://web.archive.org/web/20220129214631/http://www.thomaswong.net/introduction-to-classical-and-quantum-computing-1e.pdf }}
* {{cite book |last1=Zeng |first1=Bei |last2=Chen |first2=Xie |last3=Zhou |first3=Duan-Lu |last4=Wen |first4=Xiao-Gang |title=Quantum Information Meets Quantum Matter |year=2019 |oclc=1091358969 |isbn=978-1-4939-9084-9 |doi=10.1007/978-1-4939-9084-9 |arxiv=1508.02595 |s2cid=118528258 }}

===Academic papers===
*{{cite journal | last1=Abbot |first1=Derek |last2=Doering |first2=Charles R. |last3=Caves |first3=Carlton M. |author4-link=Daniel Lidar |last4=Lidar |first4=Daniel M. |author5-link= Howard Brandt|last5=Brandt |first5=Howard E. |author6-link= Alexander R. Hamilton |last6=Hamilton |first6=Alexander R. |author7-link=David K. Ferry |last7=Ferry |first7=David K. |author8-link=Julio Gea-Banacloche |last8=Gea-Banacloche |first8=Julio |author9-link=Sergey M. Bezrukov |last9=Bezrukov |first9=Sergey M. |author10-link=Laszlo B. Kish |first10=Laszlo B. |last10=Kish |display-authors=5 |title=Dreams versus Reality: Plenary Debate Session on Quantum Computing |journal=Quantum Information Processing |year=2003 |volume=2 |issue=6 |pages=449–472 |doi=10.1023/B:QINP.0000042203.24782.9a | arxiv=quant-ph/0310130 |bibcode=2003QuIP....2..449A |hdl=2027.42/45526|s2cid=34885835 }}
*{{cite book |last=Berthiaume |first=Andre |title=Solution Manual for Quantum Mechanics |date=1 December 1998 |chapter=Quantum Computation |s2cid=128255429 |doi=10.1142/9789814541893_0016 |via=Semantic Scholar|pages=233–234 |isbn=978-981-4541-88-6 }}
*{{Cite journal |last1=DiVincenzo |first1=David P. |title=The Physical Implementation of Quantum Computation|journal=Fortschritte der Physik |volume=48|issue=9–11|pages=771–783|year=2000 |doi=10.1002/1521-3978(200009)48:9/11<771::AID-PROP771>3.0.CO;2-E |arxiv=quant-ph/0002077 |bibcode=2000ForPh..48..771D |s2cid=15439711 }}
*{{cite journal |last=DiVincenzo |first=David P. |title=Quantum Computation |journal=Science |year=1995 |volume=270 |issue=5234 |pages=255–261 |doi= 10.1126/science.270.5234.255 |bibcode = 1995Sci...270..255D |citeseerx=10.1.1.242.2165 |s2cid=220110562 }} Table 1 lists switching and dephasing times for various systems.
*{{cite journal |last=Jeutner |first=Valentin |title=The Quantum Imperative: Addressing the Legal Dimension of Quantum Computers |journal=Morals & Machines |volume=1 |pages=52–59 |year=2021 |doi=10.5771/2747-5174-2021-1-52 |issue=1 |s2cid=236664155 |url=https://lup.lub.lu.se/record/e034e7b7-d17c-4863-9cee-7e654f97225b |doi-access=free }}
*{{Cite journal |last1=Krantz |first1=P. |last2=Kjaergaard |first2=M. |last3=Yan |first3=F. |last4=Orlando |first4=T. P. |last5=Gustavsson |first5=S. |last6=Oliver |first6=W. D. |date=2019-06-17 |title=A Quantum Engineer's Guide to Superconducting Qubits |journal=[[Physics:Applied Physics Reviews|Applied Physics Reviews]] |language=en |volume=6 |issue=2 |page=021318 |doi=10.1063/1.5089550 |arxiv=1904.06560 |bibcode=2019ApPRv...6b1318K |s2cid=119104251 |issn=1931-9401}}
*{{cite web |last=Mitchell |first=Ian |year=1998 |title=Computing Power into the 21st Century: Moore's Law and Beyond |url=http://citeseer.ist.psu.edu/mitchell98computing.html }}
*{{cite web |last = Simon |first = Daniel R. |year = 1994 |title = On the Power of Quantum Computation |publisher = Institute of Electrical and Electronics Engineers Computer Society Press |url = http://citeseer.ist.psu.edu/simon94power.html }}
{{Refend}}

== External links ==
* [[Stanford Encyclopedia of Philosophy]]: "[https://plato.stanford.edu/entries/qt-quantcomp/ Quantum Computing]" by Amit Hagar and Michael E. Cuffaro
* {{springer|title=Quantum computation, theory of|id=p/q130020}}
* [https://introtoquantum.org Introduction to Quantum Computing for Business by Koen Groenland]
* Schneider, J., & Smalley, I. (2024, August 5). ''What Is Quantum Computing? | IBM''. https://www.ibm.com/think/topics/quantum-computing

;Lectures
* [https://www.youtube.com/playlist?list=PL1826E60FD05B44E4 Quantum computing for the determined] – 22 video lectures by [[Biography:Michael Nielsen|Michael Nielsen]]
* [http://www.quiprocone.org/Protected/DD_lectures.htm Video Lectures] {{Webarchive|url=https://web.archive.org/web/20100210151240/http://www.quiprocone.org/Protected/DD_lectures.htm |date=10 February 2010 }} by [[Biography:David Deutsch|David Deutsch]]
* Lomonaco, Sam. [http://www.csee.umbc.edu/~lomonaco/Lectures.html#OxfordLectures Four Lectures on Quantum Computing given at Oxford University in July 2006]

{{CPU technologies}}
{{Quantum computing}}
{{emerging technologies|quantum=yes|other=yes}}
{{Quantum mechanics topics}}


[[Category:Quantum computing]]
[[Category:Models of computation]]
[[Category:Quantum cryptography]]
[[Category:Information theory]]
[[Category:Computational complexity theory]]
[[Category:Classes of computers]]
[[Category:Theoretical computer science]]
[[Category:Open problems]]
[[Category:Supercomputers]]

{{Sourceattribution|Quantum computing}}