8 results · ● Live web index
nature.com article

Artificial intelligence for quantum computing | Nature Communications

https://www.nature.com/articles/s41467-025-65836-3

[Article](https://doi.org/10.1103%2FPRXQuantum.3.020332)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2022PRXQ....3b0332C)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Quantum%20lego%3A%20building%20quantum%20error%20correction%20codes%20from%20tensor%20networks&journal=PRX%20Quantum&doi=10.1103%2FPRXQuantum.3.020332&volume=3&publication_year=2022&author=Cao%2CC&author=Lackey%2CB). [Article](https://doi.org/10.1103%2FPhysRevLett.114.200501)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2015PhRvL.114t0501M)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=26047215)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Machine%20learning%20for%20discriminating%20quantum%20measurement%20trajectories%20and%20improving%20readout&journal=Phys.%20Rev.%20Lett.&doi=10.1103%2FPhysRevLett.114.200501&volume=114&publication_year=2015&author=Magesan%2CE&author=Gambetta%2CJM&author=C%C3%B3rcoles%2CAD&author=Chow%2CJM). [Article](https://doi.org/10.1103%2FPhysRevApplied.17.014024)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2022PhRvP..17a4024L)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB38Xjt1yrsbw%3D)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Deep-neural-network%20discrimination%20of%20multiplexed%20superconducting-qubit%20states&journal=Phys.%20Rev.%20Appl.&doi=10.1103%2FPhysRevApplied.17.014024&volume=17&publication_year=2022&author=Lienhard%2CB). [Article](https://doi.org/10.1103%2FPhysRevApplied.22.024011)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2024PhRvP..22b4011P)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB2cXit1yhurrO)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Enhanced%20measurement%20of%20neutral-atom%20qubits%20with%20machine%20learning&journal=Phys.%20Rev.%20Appl.&doi=10.1103%2FPhysRevApplied.22.024011&volume=22&publication_year=2024&author=Phuttitarn%2CL&author=Becker%2CB&author=Chinnarasu%2CR&author=Graham%2CT&author=Saffman%2CM). [Article](https://doi.org/10.1088%2F1361-6455%2Faad62b)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2018JPhB...51q4006S)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Machine%20learning%20assisted%20readout%20of%20trapped-ion%20qubits&journal=J.%20Phys.%20B%20At.%20Mol.%20Opt.%20Phys.&doi=10.1088%2F1361-6455%2Faad62b&volume=51&publication_year=2018&author=Seif%2CA). [Article](https://doi.org/10.1038%2Fs42254-023-00662-4)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=A%20survey%20on%20the%20complexity%20of%20learning%20quantum%20states&journal=Nat.%20Rev.%20Phys.&doi=10.1038%2Fs42254-023-00662-4&volume=6&pages=59-69&publication_year=2024&author=Anshu%2CA&author=Arunachalam%2CS). [Article](https://doi.org/10.1038%2Fs41598-021-95562-x)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2021NatSR..1116203S)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB3MXhvVWisLfM)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=34376730)  [PubMed Central](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355192)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Robust%20and%20fast%20post-processing%20of%20single-shot%20spin%20qubit%20detection%20events%20with%20a%20neural%20network&journal=Sci.%20Rep.&doi=10.1038%2Fs41598-021-95562-x&volume=11&publication_year=2021&author=Struck%2CT). [Article](https://doi.org/10.1038%2Fs41534-022-00621-4)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2022npjQI...8..115S)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Efficient%20quantum%20state%20tomography%20with%20convolutional%20neural%20networks&journal=NPJ%20Quantum%20Inf.&doi=10.1038%2Fs41534-022-00621-4&volume=8&publication_year=2022&author=Schmale%2CT&author=Reh%2CM&author=G%C3%A4rttner%2CM). [Article](https://doi.org/10.1038%2Fs41534-021-00436-9)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2021npjQI...7..105Q)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Adaptive%20quantum%20state%20tomography%20with%20neural%20networks&journal=NPJ%20Quantum%20Inf.&doi=10.1038%2Fs41534-021-00436-9&volume=7&publication_year=2021&author=Quek%2CY&author=Fort%2CS&author=Ng%2CHK). [Article](https://doi.org/10.1103%2FPhysRevLett.133.120802)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2024PhRvL.133l0802C)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=4806889)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB2MXhs1Wht74%3D)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=39373411)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Efficient%20characterization%20of%20qudit%20logical%20gates%20with%20gate%20set%20tomography%20using%20an%20error-free%20virtual%20z%20gate%20model&journal=Phys.%20Rev.%20Lett.&doi=10.1103%2FPhysRevLett.133.120802&volume=133&publication_year=2024&author=Cao%2CS). [Article](https://doi.org/10.1103%2FPRXQuantum.3.020335)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2022PRXQ....3b0335B)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=A%20taxonomy%20of%20small%20markovian%20errors&journal=PRX%20Quantum&doi=10.1103%2FPRXQuantum.3.020335&volume=3&publication_year=2022&author=Blume-Kohout%2CR). [Article](https://doi.org/10.1103%2FPRXQuantum.4.010325)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2023PRXQ....4a0325B)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Compressive%20gate%20set%20tomography&journal=PRX%20Quantum&doi=10.1103%2FPRXQuantum.4.010325&volume=4&publication_year=2023&author=Brieger%2CR&author=Roth%2CI&author=Kliesch%2CM). [Article](https://doi.org/10.1103%2FPhysRevA.98.062339)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2018PhRvA..98f2339B)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BC1MXkvFOlu7Y%3D)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Low-cost%20error%20mitigation%20by%20symmetry%20verification&journal=Phys.%20Rev.%20A&doi=10.1103%2FPhysRevA.98.062339&volume=98&publication_year=2018&author=Bonet-Monroig%2CX&author=Sagastizabal%2CR&author=Singh%2CM&author=O%E2%80%99Brien%2CTE). [Article](https://doi.org/10.1103%2FPhysRevLett.122.180501)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2019PhRvL.122r0501M)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BC1MXhtFKls7fL)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=31144882)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Error-mitigated%20digital%20quantum%20simulation&journal=Phys.%20Rev.%20Lett.&doi=10.1103%2FPhysRevLett.122.180501&volume=122&publication_year=2019&author=McArdle%2CS&author=Yuan%2CX&author=Benjamin%2CS). [Article](https://doi.org/10.1103%2FPhysRevLett.119.180509)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2017PhRvL.119r0509T)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=3730724)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=29219599)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Error%20mitigation%20for%20short-depth%20quantum%20circuits&journal=Phys.%20Rev.%20Lett.&doi=10.1103%2FPhysRevLett.119.180509&volume=119&publication_year=2017&author=Temme%2CK&author=Bravyi%2CS&author=Gambetta%2CJM). [Article](https://doi.org/10.1103%2FPhysRevA.95.042308)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2017PhRvA..95d2308M)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Hybrid%20quantum-classical%20hierarchy%20for%20mitigation%20of%20decoherence%20and%20determination%20of%20excited%20states&journal=Phys.%20Rev.%20A&doi=10.1103%2FPhysRevA.95.042308&volume=95&publication_year=2017&author=McClean%2CJR&author=Kimchi-Schwartz%2CME&author=Carter%2CJ&author=Jong%2CWA). [Article](https://doi.org/10.1103%2FPRXQuantum.2.040330)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2021PRXQ....2d0330S)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Learning-based%20quantum%20error%20mitigation&journal=PRX%20Quantum&doi=10.1103%2FPRXQuantum.2.040330&volume=2&publication_year=2021&author=Strikis%2CA&author=Qin%2CD&author=Chen%2CY&author=Benjamin%2CSC&author=Li%2CY). [Article](https://doi.org/10.1103%2FRevModPhys.95.045005)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2023RvMP...95d5005C)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=4704107)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Quantum%20error%20mitigation&journal=Rev.%20Mod.%20Phys.&doi=10.1103%2FRevModPhys.95.045005&volume=95&publication_year=2023&author=Cai%2CZ). [Article](https://doi.org/10.1038%2Fs41534-024-00878-x)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2024npjQI..10..105Z)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Data%20needs%20and%20challenges%20for%20quantum%20dot%20devices%20automation&journal=NPJ%20Quantum%20Inf.&doi=10.1038%2Fs41534-024-00878-x&volume=10&publication_year=2024&author=Zwolak%2CJP). [Article](https://doi.org/10.1073%2Fpnas.17.5.315)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=1931PNAS...17..315K)  [CAS](/articles/cas-redirect/1:STN:280:DC%2BD28zhslOlsQ%3D%3D)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=16577368)  [PubMed Central](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1076052)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Hamiltonian%20systems%20and%20transformation%20in%20hilbert%20space&journal=Proc.%20Natl.%20Acad.%20Sci.%20USA&doi=10.1073%2Fpnas.17.5.315&volume=17&pages=315-318&publication_year=1931&author=Koopman%2CBO). [Article](https://link.springer.com/doi/10.1007/BF01011339)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=1980JSP....22..563B)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=574722)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=The%20computer%20as%20a%20physical%20system%3A%20A%20microscopic%20quantum%20mechanical%20Hamiltonian%20model%20of%20computers%20as%20represented%20by%20Turing%20machines&journal=J.%20Stat.%20Phys.&doi=10.1007%2FBF01011339&volume=22&pages=563-591&publication_year=1980&author=Benioff%2CP). [Article](https://link.springer.com/doi/10.1007/BF01342185)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=1982JSP....29..515B)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=704586)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Quantum%20mechanical%20hamiltonian%20models%20of%20turing%20machines&journal=J.%20Stat.%20Phys.&doi=10.1007%2FBF01342185&volume=29&pages=515-546&publication_year=1982&author=Benioff%2CP). [Article](https://doi.org/10.1103%2FPhysRevLett.116.250501)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2016PhRvL.116y0501B)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=27391708)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Improved%20classical%20simulation%20of%20quantum%20circuits%20dominated%20by%20clifford%20gates&journal=Phys.%20Rev.%20Lett.&doi=10.1103%2FPhysRevLett.116.250501&volume=116&publication_year=2016&author=Bravyi%2CS&author=Gosset%2CD). [Article](https://doi.org/10.1126%2Fscience.aag2302)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2017Sci...355..602C)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=3642415)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BC2sXit1Okur0%3D)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=28183973)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Solving%20the%20quantum%20many-body%20problem%20with%20artificial%20neural%20networks&journal=Science&doi=10.1126%2Fscience.aag2302&volume=355&pages=602-606&publication_year=2017&author=Carleo%2CG&author=Troyer%2CM). [Article](https://doi.org/10.21468%2FSciPostPhys.10.6.147)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2021ScPP...10..147B)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Learning%20the%20ground%20state%20of%20a%20non-stoquastic%20quantum%20hamiltonian%20in%20a%20rugged%20neural%20network%20landscape&journal=SciPost%20Phys.&doi=10.21468%2FSciPostPhys.10.6.147&volume=10&publication_year=2021&author=Bukov%2CM&author=Schmitt%2CM&author=Dupont%2CM). [Article](https://doi.org/10.1103%2FPhysRevA.104.062404)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2021PhRvA.104f2404H)  [MathSciNet](http://www.ams.org/mathscinet-getitem?mr=4359324)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB38XhtVGls7o%3D)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Tomography%20of%20time-dependent%20quantum%20hamiltonians%20with%20machine%20learning&journal=Phys.%20Rev.%20A&doi=10.1103%2FPhysRevA.104.062404&volume=104&publication_year=2021&author=Han%2CC-D&author=Glaz%2CB&author=Haile%2CM&author=Lai%2CY-C). [Article](https://doi.org/10.1038%2Fs41586-022-05172-4)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2022Natur.610...47F)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB38XisFygurfK)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=36198780)  [PubMed Central](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534758)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=Discovering%20faster%20matrix%20multiplication%20algorithms%20with%20reinforcement%20learning&journal=Nature&doi=10.1038%2Fs41586-022-05172-4&volume=610&pages=47-53&publication_year=2022&author=Fawzi%2CA). [Article](https://doi.org/10.1038%2Fs41598-021-91035-3)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2021NatSR..1113138X)  [CAS](/articles/cas-redirect/1:CAS:528:DC%2BB3MXhsF2hsLrP)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=34162898)  [PubMed Central](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222304)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=A%20stochastic%20quantum%20program%20synthesis%20framework%20based%20on%20bayesian%20optimization&journal=Sci.%20Rep.&doi=10.1038%2Fs41598-021-91035-3&volume=11&publication_year=2021&author=Xiao%2CY&author=Nazarian%2CS&author=Bogdan%2CP). [Article](https://doi.org/10.1088%2F1367-2630%2F16%2F7%2F073017)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=A%20strategy%20for%20quantum%20algorithm%20design%20assisted%20by%20machine%20learning&journal=N.%20J.%20Phys.&doi=10.1088%2F1367-2630%2F16%2F7%2F073017&volume=16&publication_year=2014&author=Bang%2CJ&author=Ryu%2CJ&author=Yoo%2CS&author=Paw%C5%82owski%2CM&author=Lee%2CJ). [Article](https://doi.org/10.1038%2Fs41467-019-10988-2)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2019NatCo..10.3007G)  [PubMed](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Abstract&list_uids=31285433)  [PubMed Central](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6614426)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=An%20adaptive%20variational%20algorithm%20for%20exact%20molecular%20simulations%20on%20a%20quantum%20computer&journal=Nat.%20Commun.&doi=10.1038%2Fs41467-019-10988-2&volume=10&publication_year=2019&author=Grimsley%2CHR&author=Economou%2CSE&author=Barnes%2CE&author=Mayhall%2CNJ). [Article](https://doi.org/10.1063%2F1.5088412)  [ADS](http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=2019ApPhL.114m3102T)  [Google Scholar](http://scholar.google.com/scholar_lookup?&title=A%20machine%20learning%20approach%20for%20automated%20fine-tuning%20of%20semiconductor%20spin%20qubits&journal=Appl.%20Phys.%20Lett.&doi=10.1063%2F1.5088412&volume=114&publication_year=2019&author=Teske%2CJD).

Visit
uts.edu.au research

AI and machine learning take a quantum leap - UTS

https://www.uts.edu.au/stories/ai-and-machine-learning-take-a-quantum-leap

Professor Chris Ferrie studies how AI, machine learning and information systems will play out in the age of quantum computing.

Visit
medium.com article

Can Quantum Computing accelerate Generative AI? | by Alexander Del Toro Barba (PhD) | Medium

https://medium.com/@deltorobarba/can-quantum-computing-accelerate-generative-…

Examples for (1) are the fundamental question posed in this article: can we use quantum computers to accelerate classical machine learning? Examples for (3) include cases where either classical ML helps to improve quantum computers (finding better algorithms or quantum circuits), to using classical shadow tomography on quantum data to learn new things. Ideally one can prove with methods from complexity theory that classical methods will never be able to achieve the same efficiency as a quantum machine learning algorithm. This brings us to the next challenge: if you use classical data, many QML algorithms expect data in a certain format in qRAM and Ewin Tang demonstrated that the class of quantum algorithms that uses state preparation assumptions implicitly require having matrices of low rank and this equals classical 𝓁²-norm sampling assumptions with a small polynomial overhead, meaning you can dequantize them (her PhD thesis with the title: Quantum Machine Learning without any Quantum :).

Visit
en.wikipedia.org article

Quantum machine learning - Wikipedia

https://en.wikipedia.org/wiki/Quantum_machine_learning

A number of quantum algorithms for machine learning are based on the idea of amplitude encoding, that is, to associate the [amplitudes](/wiki/Probability_amplitude "Probability amplitude") of a quantum state with the inputs and outputs of computations.[[30]](#cite_note-Patrick_Rebentrost_2014-30)[[31]](#cite_note-Nathan_Wiebe_2012-31)[[32]](#cite_note-Maria_Schuld_2016-32) Since a state of n {\displaystyle n} ![{\displaystyle n}](https://wikimedia.org/api/rest_v1/media/math/render/svg/a601995d55609f2d9f5e233e36fbe9ea26011b3b) qubits is described by 2 n {\displaystyle 2^{n}} ![{\displaystyle 2^{n}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/8226f30650ee4fe4e640c6d2798127e80e9c160d) complex amplitudes, this information encoding can allow for an exponentially compact representation. One of these conditions is that a [Hamiltonian](/wiki/Hamiltonian_(quantum_mechanics) "Hamiltonian (quantum mechanics)") which entry-wise corresponds to the matrix can be simulated efficiently, which is known to be possible if the matrix is sparse[[34]](#cite_note-34) or low rank.[[35]](#cite_note-35) For reference, any known classical algorithm for [matrix inversion](/wiki/Matrix_inversion "Matrix inversion") requires a number of operations that grows [more than quadratically in the dimension of the matrix](/wiki/Computational_complexity_of_mathematical_operations#Matrix_algebra "Computational complexity of mathematical operations") (e.g. O ( n 2.373 ) {\displaystyle O{\mathord {\left(n^{2.373}\right)}}} ![{\displaystyle O{\mathord {\left(n^{2.373}\right)}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/1aae64872678cfd84c60f52b8c789d8d67141fb0)), but they are not restricted to sparse matrices. **[^](#cite_ref-118)** ["Can quantum machine learning move beyond its own hype?"](https://www.quantamagazine.org/job-one-for-quantum-computers-boost-artificial-intelligence-20180129/).

Visit
research.ibm.com research

Quantum Machine Learning - IBM Research

https://research.ibm.com/topics/quantum-machine-learning

We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug

Visit
People also search for
Recent Breakthroughs in Quantum AI and Machine Learning Quantum Computing Applications in Artificial Intelligence Machine Learning with Quantum Computing Architectures Advancements in Quantum AI Models and Algorithms Quantum Machine Learning for Natural Language Processing