Near-term quantum algorithms for linear systems of equations with regression loss functions
Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum resources are not immediately available on near-term quantum...
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| Vydané v: | New journal of physics Ročník 23; číslo 11; s. 113021 - 113047 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Bristol
IOP Publishing
01.11.2021
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| ISSN: | 1367-2630, 1367-2630 |
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| Abstract | Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum resources are not immediately available on near-term quantum devices. In this work, we study near-term quantum algorithms for linear systems of equations, with a focus on the two-norm and Tikhonov regression settings. We investigate the use of variational algorithms and analyze their optimization landscapes. There exist types of linear systems for which variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, suffer from a different plateau problem. To circumvent this issue, we design near-term algorithms based on a core idea: the classical combination of variational quantum states (CQS). We exhibit several provable guarantees for these algorithms, supported by the representation of the linear system on a so-called ansatz tree. The CQS approach and the ansatz tree also admit the systematic application of heuristic approaches, including a gradient-based search. We have conducted numerical experiments solving linear systems as large as 2
300
× 2
300
by considering cases where we can simulate the quantum algorithm efficiently on a classical computer. Our methods may provide benefits for solving linear systems within the reach of near-term quantum devices. |
|---|---|
| AbstractList | Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum resources are not immediately available on near-term quantum devices. In this work, we study near-term quantum algorithms for linear systems of equations, with a focus on the two-norm and Tikhonov regression settings. We investigate the use of variational algorithms and analyze their optimization landscapes. There exist types of linear systems for which variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, suffer from a different plateau problem. To circumvent this issue, we design near-term algorithms based on a core idea: the classical combination of variational quantum states (CQS). We exhibit several provable guarantees for these algorithms, supported by the representation of the linear system on a so-called ansatz tree. The CQS approach and the ansatz tree also admit the systematic application of heuristic approaches, including a gradient-based search. We have conducted numerical experiments solving linear systems as large as 2
300
× 2
300
by considering cases where we can simulate the quantum algorithm efficiently on a classical computer. Our methods may provide benefits for solving linear systems within the reach of near-term quantum devices. Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum resources are not immediately available on near-term quantum devices. In this work, we study near-term quantum algorithms for linear systems of equations, with a focus on the two-norm and Tikhonov regression settings. We investigate the use of variational algorithms and analyze their optimization landscapes. There exist types of linear systems for which variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, suffer from a different plateau problem. To circumvent this issue, we design near-term algorithms based on a core idea: the classical combination of variational quantum states (CQS). We exhibit several provable guarantees for these algorithms, supported by the representation of the linear system on a so-called ansatz tree. The CQS approach and the ansatz tree also admit the systematic application of heuristic approaches, including a gradient-based search. We have conducted numerical experiments solving linear systems as large as 2 ^300 × 2 ^300 by considering cases where we can simulate the quantum algorithm efficiently on a classical computer. Our methods may provide benefits for solving linear systems within the reach of near-term quantum devices. Solving linear systems of equations is essential for many problems in science and technology, including problems in machine learning. Existing quantum algorithms have demonstrated the potential for large speedups, but the required quantum resources are not immediately available on near-term quantum devices. In this work, we study near-term quantum algorithms for linear systems of equations, with a focus on the two-norm and Tikhonov regression settings. We investigate the use of variational algorithms and analyze their optimization landscapes. There exist types of linear systems for which variational algorithms designed to avoid barren plateaus, such as properly-initialized imaginary time evolution and adiabatic-inspired optimization, suffer from a different plateau problem. To circumvent this issue, we design near-term algorithms based on a core idea: the classical combination of variational quantum states (CQS). We exhibit several provable guarantees for these algorithms, supported by the representation of the linear system on a so-called ansatz tree. The CQS approach and the ansatz tree also admit the systematic application of heuristic approaches, including a gradient-based search. We have conducted numerical experiments solving linear systems as large as 2300 × 2300 by considering cases where we can simulate the quantum algorithm efficiently on a classical computer. Our methods may provide benefits for solving linear systems within the reach of near-term quantum devices. |
| Author | Rebentrost, Patrick Huang, Hsin-Yuan Bharti, Kishor |
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| Cites_doi | 10.1103/physrevlett.118.010501 10.1137/s1052623496303470 10.1103/physrevx.7.021050 10.1126/science.273.5278.1073 10.22331/q-2019-05-13-140 10.1021/j100342a008 10.1002/qua.560120850 10.1038/s41567-018-0318-2 10.1088/1367-2630/18/2/023023 10.1038/s41586-019-1666-5 10.1126/science.aao4309 10.1080/00401706.1970.10488634 10.1103/physrevlett.122.060504 10.1007/s00220-016-2706-8 10.22331/q-2019-07-12-163 10.1103/physrevx.8.011021 10.22331/q-2018-08-06-79 10.1063/1.1727484 10.1007/s11128-020-02748-9 10.1063/1.443164 10.1214/15-aop1025 10.3390/a12020034 10.1038/s41534-019-0167-6 10.1038/s41467-018-07090-4 10.1103/physrevlett.103.150502 10.1137/16m1087072 10.1126/science.abe8770 10.1038/nature23458 10.1103/physreva.97.022304 10.1103/physrevlett.114.090502 10.1103/physreva.92.042303 10.1038/nature23879 10.1038/s41534-019-0187-2 10.1088/2058-9565/aab822 10.1038/ncomms5213 10.1103/physrevx.6.031007 |
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| References | Bartlett (njpac325fbib58) 1989; 93 Preskill (njpac325fbib7) 2018; 2 Bharti (njpac325fbib16) 2021 Bravo-Prieto (njpac325fbib30) 2019 Colless (njpac325fbib52) 2018; 8 Hadfield (njpac325fbib45) 2019; 12 Bouland (njpac325fbib15) 2019; 15 Lagarias (njpac325fbib31) 1998; 9 Harrow (njpac325fbib1) 2009; 103 Farhi (njpac325fbib34) 2000 McArdle (njpac325fbib41) 2018 Cerezo (njpac325fbib17) 2020 Low (njpac325fbib26) 2017; 118 Preskill (njpac325fbib8) 2012 Purvis (njpac325fbib57) 1982; 76 Subaşı (njpac325fbib29) 2019; 122 Ng (njpac325fbib39) 2004 Berry (njpac325fbib36) 2015 LaRose (njpac325fbib59) 2019; 5 van Apeldoorn (njpac325fbib4) 2017 Farhi (njpac325fbib22) 2016 Bandeira (njpac325fbib46) 2016; 44 An (njpac325fbib28) 2019 Hoerl (njpac325fbib40) 1970; 12 Aaronson (njpac325fbib9) 2016 Aaronson (njpac325fbib14) 2011 Harrow (njpac325fbib10) 2017; 549 Xu (njpac325fbib37) 2019 Monkhorst (njpac325fbib56) 1977; 12 Li (njpac325fbib5) 2019 Neill (njpac325fbib11) 2018; 360 Kandala (njpac325fbib20) 2017; 549 Boyd (njpac325fbib49) 2004 Berry (njpac325fbib24) 2015; 114 O’Malley (njpac325fbib51) 2016; 6 Chia (njpac325fbib50) 2019 Brandão (njpac325fbib61) 2016; 346 Farhi (njpac325fbib21) 2014 Zhong (njpac325fbib13) 2020; 370 Morales (njpac325fbib63) 2020; 19 McClean (njpac325fbib38) 2018; 9 Childs (njpac325fbib23) 2015 Li (njpac325fbib32) 2017; 7 McArdle (njpac325fbib33) 2019; 5 Arute (njpac325fbib12) 2019; 574 Low (njpac325fbib27) 2019; 3 Khatri (njpac325fbib60) 2019; 3 Wang (njpac325fbib54) 2018; 97 van Apeldoorn (njpac325fbib2) 2018 Lloyd (njpac325fbib35) 1996; 273 Chakrabarti (njpac325fbib3) 2018 Čížek (njpac325fbib55) 1966; 45 Childs (njpac325fbib47) 2017; 46 Nocedal (njpac325fbib48) 2006 Smith (njpac325fbib44) 2016 Brandão (njpac325fbib6) 2019 Garcia-Saez (njpac325fbib43) 2018 Wecker (njpac325fbib42) 2015; 92 Gilyén (njpac325fbib25) 2019 Peruzzo (njpac325fbib18) 2014; 5 McClean (njpac325fbib19) 2016; 18 Lloyd (njpac325fbib62) 2018 Moll (njpac325fbib53) 2018; 3 |
| References_xml | – start-page: p 78 year: 2004 ident: njpac325fbib39 – year: 2014 ident: njpac325fbib21 – year: 2016 ident: njpac325fbib44 article-title: A practical quantum instruction set architecture – volume: 118 year: 2017 ident: njpac325fbib26 publication-title: Phys. Rev. Lett. doi: 10.1103/physrevlett.118.010501 – volume: 9 start-page: 112 year: 1998 ident: njpac325fbib31 publication-title: SIAM J. Optim. doi: 10.1137/s1052623496303470 – volume: 7 year: 2017 ident: njpac325fbib32 publication-title: Phys. Rev. X doi: 10.1103/physrevx.7.021050 – year: 2020 ident: njpac325fbib17 – year: 2019 ident: njpac325fbib28 – volume: 273 start-page: 1073 year: 1996 ident: njpac325fbib35 publication-title: Science doi: 10.1126/science.273.5278.1073 – volume: 3 start-page: 140 year: 2019 ident: njpac325fbib60 publication-title: Quantum doi: 10.22331/q-2019-05-13-140 – year: 2018 ident: njpac325fbib43 – volume: 93 start-page: 1697 year: 1989 ident: njpac325fbib58 publication-title: J. Phys. Chem. doi: 10.1021/j100342a008 – year: 2015 ident: njpac325fbib36 – volume: 12 start-page: 421 year: 1977 ident: njpac325fbib56 publication-title: Int. J. Quantum Chem. doi: 10.1002/qua.560120850 – year: 2018 ident: njpac325fbib62 – volume: 15 start-page: 159 year: 2019 ident: njpac325fbib15 publication-title: Nat. Phys. doi: 10.1038/s41567-018-0318-2 – volume: 18 year: 2016 ident: njpac325fbib19 publication-title: New J. Phys. doi: 10.1088/1367-2630/18/2/023023 – volume: 574 start-page: 505 year: 2019 ident: njpac325fbib12 publication-title: Nature doi: 10.1038/s41586-019-1666-5 – volume: 360 start-page: 195 year: 2018 ident: njpac325fbib11 publication-title: Science doi: 10.1126/science.aao4309 – year: 2006 ident: njpac325fbib48 – volume: 12 start-page: 55 year: 1970 ident: njpac325fbib40 publication-title: Technometrics doi: 10.1080/00401706.1970.10488634 – volume: 122 year: 2019 ident: njpac325fbib29 publication-title: Phys. Rev. Lett. doi: 10.1103/physrevlett.122.060504 – volume: 346 start-page: 397 year: 2016 ident: njpac325fbib61 publication-title: Commun. Math. Phys. doi: 10.1007/s00220-016-2706-8 – year: 2019 ident: njpac325fbib6 – volume: 3 start-page: 163 year: 2019 ident: njpac325fbib27 publication-title: Quantum doi: 10.22331/q-2019-07-12-163 – volume: 8 year: 2018 ident: njpac325fbib52 publication-title: Phys. Rev. X doi: 10.1103/physrevx.8.011021 – year: 2021 ident: njpac325fbib16 – year: 2019 ident: njpac325fbib25 – year: 2015 ident: njpac325fbib23 – volume: 2 start-page: 79 year: 2018 ident: njpac325fbib7 publication-title: Quantum doi: 10.22331/q-2018-08-06-79 – volume: 45 start-page: 4256 year: 1966 ident: njpac325fbib55 publication-title: J. Chem. Phys. doi: 10.1063/1.1727484 – volume: 19 start-page: 291 year: 2020 ident: njpac325fbib63 publication-title: Quant. Inf. Process. doi: 10.1007/s11128-020-02748-9 – volume: 76 start-page: 1910 year: 1982 ident: njpac325fbib57 publication-title: J. Chem. Phys. doi: 10.1063/1.443164 – year: 2019 ident: njpac325fbib50 – volume: 44 start-page: 2479 year: 2016 ident: njpac325fbib46 publication-title: Ann. Probab. doi: 10.1214/15-aop1025 – volume: 12 start-page: 34 year: 2019 ident: njpac325fbib45 publication-title: Algorithms doi: 10.3390/a12020034 – year: 2018 ident: njpac325fbib3 – year: 2019 ident: njpac325fbib37 – volume: 5 start-page: 8 year: 2019 ident: njpac325fbib59 publication-title: npj Quantum Information doi: 10.1038/s41534-019-0167-6 – volume: 9 start-page: 4812 year: 2018 ident: njpac325fbib38 publication-title: Nat. Commun. doi: 10.1038/s41467-018-07090-4 – year: 2018 ident: njpac325fbib2 – year: 2000 ident: njpac325fbib34 – volume: 103 year: 2009 ident: njpac325fbib1 publication-title: Phys. Rev. Lett. doi: 10.1103/physrevlett.103.150502 – volume: 46 start-page: 1920 year: 2017 ident: njpac325fbib47 publication-title: SIAM J. Comput. doi: 10.1137/16m1087072 – year: 2011 ident: njpac325fbib14 – year: 2019 ident: njpac325fbib30 – volume: 370 start-page: 1460 year: 2020 ident: njpac325fbib13 publication-title: Science doi: 10.1126/science.abe8770 – year: 2016 ident: njpac325fbib22 – year: 2019 ident: njpac325fbib5 – year: 2017 ident: njpac325fbib4 – volume: 549 start-page: 203 year: 2017 ident: njpac325fbib10 publication-title: Nature doi: 10.1038/nature23458 – year: 2018 ident: njpac325fbib41 – volume: 97 year: 2018 ident: njpac325fbib54 publication-title: Phys. Rev. A doi: 10.1103/physreva.97.022304 – volume: 114 year: 2015 ident: njpac325fbib24 publication-title: Phys. Rev. Lett. doi: 10.1103/physrevlett.114.090502 – volume: 92 year: 2015 ident: njpac325fbib42 publication-title: Phys. Rev. A doi: 10.1103/physreva.92.042303 – volume: 549 start-page: 242 year: 2017 ident: njpac325fbib20 publication-title: Nature doi: 10.1038/nature23879 – volume: 5 start-page: 1 year: 2019 ident: njpac325fbib33 publication-title: npj Quantum Information doi: 10.1038/s41534-019-0187-2 – year: 2016 ident: njpac325fbib9 – year: 2004 ident: njpac325fbib49 – volume: 3 year: 2018 ident: njpac325fbib53 publication-title: Quantum Sci. Technol. doi: 10.1088/2058-9565/aab822 – year: 2012 ident: njpac325fbib8 – volume: 5 start-page: 4213 year: 2014 ident: njpac325fbib18 publication-title: Nat. Commun. doi: 10.1038/ncomms5213 – volume: 6 year: 2016 ident: njpac325fbib51 publication-title: Phys. Rev. X doi: 10.1103/physrevx.6.031007 |
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| StartPage | 113021 |
| SubjectTerms | Algorithms Heuristic methods Linear systems Machine learning Mathematical analysis near-term quantum algorithms Optimization Physics quantum computing |
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| Title | Near-term quantum algorithms for linear systems of equations with regression loss functions |
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| Volume | 23 |
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