Efficient algorithm for full-state quantum circuit simulation with DD compression while maintaining accuracy
With the development of noisy intermediate-scale quantum machines, quantum processors show their supremacy in specific applications. To better understand the quantum behavior and verify larger quantum bit (qubit) algorithms, simulation on classical computers becomes crucial. However, as the simulate...
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| Vydané v: | Quantum information processing Ročník 22; číslo 11 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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17.11.2023
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| ISSN: | 1573-1332, 1573-1332 |
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| Abstract | With the development of noisy intermediate-scale quantum machines, quantum processors show their supremacy in specific applications. To better understand the quantum behavior and verify larger quantum bit (qubit) algorithms, simulation on classical computers becomes crucial. However, as the simulated number of qubits increases, the full-state simulation suffers exponential memory increment for state vector storing. In order to compress the state vector, some existing works reduce the memory by data encoding compressors. Nevertheless, the memory requirement remains massive. Meanwhile, others utilize compact decision diagrams (DD) to represent the state vector, which only demands linear memory size. However, the existing DD-based simulation algorithm possesses many redundant calculations that require further exploration. Besides, the traditional normalization-based nodes merging method of DD amplifies the side influences of approximate error. Therefore, to tackle the above challenges, in this paper, we first fully explore the redundancies in the recursive-based DD simulation (RecurSim) algorithm. Inspired by the regularities of the quantum circuit model, a scale-based simulation (ScaleSim) algorithm is proposed, which removes plenty of unnecessary computations. Furthermore, to eliminate the influences of approximate error, we propose a new pre-check DD building method, namely PCB, which maintains the accuracy of DD representation and produces more memory saving. Comprehensive experiments show that our method achieves up to 24124.2
×
acceleration and 3.2
×
10
7
×
memory reduction than traditional DD-based methods on quantum algorithms while maintaining the representation accuracy. |
|---|---|
| AbstractList | With the development of noisy intermediate-scale quantum machines, quantum processors show their supremacy in specific applications. To better understand the quantum behavior and verify larger quantum bit (qubit) algorithms, simulation on classical computers becomes crucial. However, as the simulated number of qubits increases, the full-state simulation suffers exponential memory increment for state vector storing. In order to compress the state vector, some existing works reduce the memory by data encoding compressors. Nevertheless, the memory requirement remains massive. Meanwhile, others utilize compact decision diagrams (DD) to represent the state vector, which only demands linear memory size. However, the existing DD-based simulation algorithm possesses many redundant calculations that require further exploration. Besides, the traditional normalization-based nodes merging method of DD amplifies the side influences of approximate error. Therefore, to tackle the above challenges, in this paper, we first fully explore the redundancies in the recursive-based DD simulation (RecurSim) algorithm. Inspired by the regularities of the quantum circuit model, a scale-based simulation (ScaleSim) algorithm is proposed, which removes plenty of unnecessary computations. Furthermore, to eliminate the influences of approximate error, we propose a new pre-check DD building method, namely PCB, which maintains the accuracy of DD representation and produces more memory saving. Comprehensive experiments show that our method achieves up to 24124.2
×
acceleration and 3.2
×
10
7
×
memory reduction than traditional DD-based methods on quantum algorithms while maintaining the representation accuracy. |
| ArticleNumber | 413 |
| Author | Song, Yuhong Sha, Edwin Hsing-Mean Xu, Rui Zhuge, Qingfeng Wang, Han |
| Author_xml | – sequence: 1 givenname: Yuhong orcidid: 0000-0002-4310-2766 surname: Song fullname: Song, Yuhong organization: School of Computer Science and Technology, East China Normal University – sequence: 2 givenname: Edwin Hsing-Mean orcidid: 0000-0001-5605-5631 surname: Sha fullname: Sha, Edwin Hsing-Mean organization: School of Computer Science and Technology, East China Normal University – sequence: 3 givenname: Qingfeng orcidid: 0000-0002-1107-3470 surname: Zhuge fullname: Zhuge, Qingfeng email: qfzhuge@cs.ecnu.edu.cn organization: School of Computer Science and Technology, East China Normal University – sequence: 4 givenname: Rui surname: Xu fullname: Xu, Rui organization: School of Computer Science and Technology, East China Normal University – sequence: 5 givenname: Han surname: Wang fullname: Wang, Han organization: School of Computer Science and Technology, East China Normal University |
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| Cites_doi | 10.1145/237814.237866 10.1038/s41567-018-0124-x 10.1137/S0097539796300921 10.23919/DATE.2017.7927034 10.1016/j.cpc.2006.08.007 10.1109/SC41404.2022.00019 10.1145/3126908.3126947 10.1023/B:QINP.0000022725.70000.4a 10.1137/S0036144598347011 10.23919/DATE.2017.7927035 10.1109/TPDS.2019.2947511 10.1109/TCAD.2018.2834427 10.22331/q-2018-01-31-49 10.1038/s41586-019-1666-5 10.1038/s41467-020-20314-w 10.1109/HPCA51647.2021.00026 10.1145/3295500.3356155 10.1371/journal.pone.0206704 |
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| Keywords | Quantum circuit simulation Decision diagram Algorithm optimization Error mitigation |
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| References | BernsteinEVaziraniUQuantum complexity theorySIAM J. Comput.199726514111473147198810.1137/S00975397963009210895.68042 Shang, H., Shen, L., Fan, Y., Xu, Z., Guo, C., Liu, J., Zhou, W., Ma, H., Lin, R., Yang, Y., et al.: Large-scale simulation of quantum computational chemistry on a new Sunway supercomputer. arXiv preprint arXiv:2207.03711 (2022) LiRWuBYingMSunXYangGQuantum supremacy circuit simulation on Sunway TaihuLightIEEE Trans. Parallel Distrib. Syst.201931480581610.1109/TPDS.2019.2947511 Soeken, M., Roetteler, M., Wiebe, N., De Micheli, G.: Design automation and design space exploration for quantum computers. In: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, pp. 470–475 (2017). IEEE McCaskeyADumitrescuEChenMLyakhDHumbleTValidating quantum-classical programming models with tensor network simulationsPLoS ONE20181312020670410.1371/journal.pone.0206704 Fatima, A., Markov, I.L.: Faster schrödinger-style simulation of quantum circuits. In: 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 194–207 (2021). IEEE BoixoSIsakovSVSmelyanskiyVNBabbushRDingNJiangZBremnerMJMartinisJMNevenHCharacterizing quantum supremacy in near-term devicesNat. Phys.201814659560010.1038/s41567-018-0124-x Boixo, S., Isakov, S.V., Smelyanskiy, V.N., Neven, H.: Simulation of low-depth quantum circuits as complex undirected graphical models. arXiv preprint arXiv:1712.05384 (2017) Wu, X.-C., Di, S., Dasgupta, E.M., Cappello, F., Finkel, H., Alexeev, Y., Chong, F.T.: Full-state quantum circuit simulation by using data compression. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–24 (2019) SteigerDSHänerTTroyerMProjectQ: an open source software framework for quantum computingQuantum201824910.22331/q-2018-01-31-49 Pednault, E., Gunnels, J.A., Nannicini, G., Horesh, L., Magerlein, T., Solomonik, E., Wisnieff, R.: Breaking the 49-qubit barrier in the simulation of quantum circuits. arXiv preprint arXiv:1710.0586715 (2017) NielsenMAChuangILQuantum Computation and Quantum Information2000CambridgeCambridge University Press1049.81015 ZhouYStoudenmireEMWaintalXWhat limits the simulation of quantum computers?Phys. Rev. X2020104 Häner, T., Steiger, D.S.: 0.5 petabyte simulation of a 45-qubit quantum circuit. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–10 (2017) ViamontesGFMarkovILHayesJPImproving gate-level simulation of quantum circuitsQuantum Inf. Process.200325347380206596910.1023/B:QINP.0000022725.70000.4a1130.81341 ShorPWPolynomial-time algorithms for prime factorization and discrete logarithms on a quantum computerSIAM Rev.1999412303332168454610.1137/S00361445983470111005.115071999SIAMR..41..303S JiangWXiongJShiYA co-design framework of neural networks and quantum circuits towards quantum advantageNat. Commun.2021121113 ZulehnerAWilleRAdvanced simulation of quantum computationsIEEE Trans. Comput. Aided Des. Integr. Circuits Syst.201838584885910.1109/TCAD.2018.2834427 Khammassi, N., Ashraf, I., Fu, X., Almudever, C.G., Bertels, K.: Qx: a high-performance quantum computer simulation platform. In: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, pp. 464–469 (2017). IEEE Aaronson, S., Chen, L.: Complexity-theoretic foundations of quantum supremacy experiments. In: 32nd Computational Complexity Conference. LIPIcs, vol. 79, pp. 22–167 (2017) AruteFAryaKBabbushRBaconDBardinJCBarendsRBiswasRBoixoSBrandaoFGBuellDAQuantum supremacy using a programmable superconducting processorNature2019574777950551010.1038/s41586-019-1666-52019Natur.574..505A Smelyanskiy, M., Sawaya, N.P., Aspuru-Guzik, A.: qHiPSTER: the quantum high performance software testing environment. arXiv preprint arXiv:1601.07195 (2016) Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing, pp. 212–219 (1996) De RaedtKMichielsenKDe RaedtHTrieuBArnoldGRichterMLippertTWatanabeHItoNMassively parallel quantum computer simulatorComput. Phys. Commun.2007176212113610.1016/j.cpc.2006.08.0071196.810942007CoPhC.176..121D Y Zhou (4160_CR17) 2020; 10 A McCaskey (4160_CR9) 2018; 13 4160_CR7 4160_CR11 4160_CR8 4160_CR10 A Zulehner (4160_CR15) 2018; 38 4160_CR21 4160_CR20 S Boixo (4160_CR2) 2018; 14 W Jiang (4160_CR6) 2021; 12 4160_CR13 DS Steiger (4160_CR24) 2018; 2 4160_CR12 4160_CR23 4160_CR19 MA Nielsen (4160_CR1) 2000 PW Shor (4160_CR4) 1999; 41 E Bernstein (4160_CR16) 1997; 26 GF Viamontes (4160_CR14) 2003; 2 F Arute (4160_CR3) 2019; 574 R Li (4160_CR22) 2019; 31 4160_CR5 K De Raedt (4160_CR18) 2007; 176 |
| References_xml | – reference: Shang, H., Shen, L., Fan, Y., Xu, Z., Guo, C., Liu, J., Zhou, W., Ma, H., Lin, R., Yang, Y., et al.: Large-scale simulation of quantum computational chemistry on a new Sunway supercomputer. arXiv preprint arXiv:2207.03711 (2022) – reference: AruteFAryaKBabbushRBaconDBardinJCBarendsRBiswasRBoixoSBrandaoFGBuellDAQuantum supremacy using a programmable superconducting processorNature2019574777950551010.1038/s41586-019-1666-52019Natur.574..505A – reference: ZhouYStoudenmireEMWaintalXWhat limits the simulation of quantum computers?Phys. Rev. X2020104 – reference: Häner, T., Steiger, D.S.: 0.5 petabyte simulation of a 45-qubit quantum circuit. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–10 (2017) – reference: SteigerDSHänerTTroyerMProjectQ: an open source software framework for quantum computingQuantum201824910.22331/q-2018-01-31-49 – reference: NielsenMAChuangILQuantum Computation and Quantum Information2000CambridgeCambridge University Press1049.81015 – reference: JiangWXiongJShiYA co-design framework of neural networks and quantum circuits towards quantum advantageNat. Commun.2021121113 – reference: Smelyanskiy, M., Sawaya, N.P., Aspuru-Guzik, A.: qHiPSTER: the quantum high performance software testing environment. arXiv preprint arXiv:1601.07195 (2016) – reference: Boixo, S., Isakov, S.V., Smelyanskiy, V.N., Neven, H.: Simulation of low-depth quantum circuits as complex undirected graphical models. arXiv preprint arXiv:1712.05384 (2017) – reference: LiRWuBYingMSunXYangGQuantum supremacy circuit simulation on Sunway TaihuLightIEEE Trans. Parallel Distrib. Syst.201931480581610.1109/TPDS.2019.2947511 – reference: Soeken, M., Roetteler, M., Wiebe, N., De Micheli, G.: Design automation and design space exploration for quantum computers. In: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, pp. 470–475 (2017). IEEE – reference: BernsteinEVaziraniUQuantum complexity theorySIAM J. Comput.199726514111473147198810.1137/S00975397963009210895.68042 – reference: De RaedtKMichielsenKDe RaedtHTrieuBArnoldGRichterMLippertTWatanabeHItoNMassively parallel quantum computer simulatorComput. Phys. Commun.2007176212113610.1016/j.cpc.2006.08.0071196.810942007CoPhC.176..121D – reference: Pednault, E., Gunnels, J.A., Nannicini, G., Horesh, L., Magerlein, T., Solomonik, E., Wisnieff, R.: Breaking the 49-qubit barrier in the simulation of quantum circuits. arXiv preprint arXiv:1710.0586715 (2017) – reference: Wu, X.-C., Di, S., Dasgupta, E.M., Cappello, F., Finkel, H., Alexeev, Y., Chong, F.T.: Full-state quantum circuit simulation by using data compression. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–24 (2019) – reference: ViamontesGFMarkovILHayesJPImproving gate-level simulation of quantum circuitsQuantum Inf. Process.200325347380206596910.1023/B:QINP.0000022725.70000.4a1130.81341 – reference: Fatima, A., Markov, I.L.: Faster schrödinger-style simulation of quantum circuits. In: 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 194–207 (2021). IEEE – reference: Aaronson, S., Chen, L.: Complexity-theoretic foundations of quantum supremacy experiments. In: 32nd Computational Complexity Conference. LIPIcs, vol. 79, pp. 22–167 (2017) – reference: BoixoSIsakovSVSmelyanskiyVNBabbushRDingNJiangZBremnerMJMartinisJMNevenHCharacterizing quantum supremacy in near-term devicesNat. Phys.201814659560010.1038/s41567-018-0124-x – reference: Khammassi, N., Ashraf, I., Fu, X., Almudever, C.G., Bertels, K.: Qx: a high-performance quantum computer simulation platform. In: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, pp. 464–469 (2017). IEEE – reference: ShorPWPolynomial-time algorithms for prime factorization and discrete logarithms on a quantum computerSIAM Rev.1999412303332168454610.1137/S00361445983470111005.115071999SIAMR..41..303S – reference: Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing, pp. 212–219 (1996) – reference: McCaskeyADumitrescuEChenMLyakhDHumbleTValidating quantum-classical programming models with tensor network simulationsPLoS ONE20181312020670410.1371/journal.pone.0206704 – reference: ZulehnerAWilleRAdvanced simulation of quantum computationsIEEE Trans. Comput. Aided Des. Integr. Circuits Syst.201838584885910.1109/TCAD.2018.2834427 – ident: 4160_CR13 – ident: 4160_CR5 doi: 10.1145/237814.237866 – ident: 4160_CR12 – volume: 14 start-page: 595 issue: 6 year: 2018 ident: 4160_CR2 publication-title: Nat. Phys. doi: 10.1038/s41567-018-0124-x – volume: 26 start-page: 1411 issue: 5 year: 1997 ident: 4160_CR16 publication-title: SIAM J. Comput. doi: 10.1137/S0097539796300921 – ident: 4160_CR20 – ident: 4160_CR23 doi: 10.23919/DATE.2017.7927034 – volume: 176 start-page: 121 issue: 2 year: 2007 ident: 4160_CR18 publication-title: Comput. Phys. Commun. doi: 10.1016/j.cpc.2006.08.007 – ident: 4160_CR19 doi: 10.1109/SC41404.2022.00019 – ident: 4160_CR21 doi: 10.1145/3126908.3126947 – volume: 2 start-page: 347 issue: 5 year: 2003 ident: 4160_CR14 publication-title: Quantum Inf. Process. doi: 10.1023/B:QINP.0000022725.70000.4a – volume: 41 start-page: 303 issue: 2 year: 1999 ident: 4160_CR4 publication-title: SIAM Rev. doi: 10.1137/S0036144598347011 – ident: 4160_CR7 doi: 10.23919/DATE.2017.7927035 – volume: 31 start-page: 805 issue: 4 year: 2019 ident: 4160_CR22 publication-title: IEEE Trans. Parallel Distrib. Syst. doi: 10.1109/TPDS.2019.2947511 – volume: 38 start-page: 848 issue: 5 year: 2018 ident: 4160_CR15 publication-title: IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. doi: 10.1109/TCAD.2018.2834427 – ident: 4160_CR8 – volume-title: Quantum Computation and Quantum Information year: 2000 ident: 4160_CR1 – volume: 2 start-page: 49 year: 2018 ident: 4160_CR24 publication-title: Quantum doi: 10.22331/q-2018-01-31-49 – volume: 574 start-page: 505 issue: 7779 year: 2019 ident: 4160_CR3 publication-title: Nature doi: 10.1038/s41586-019-1666-5 – volume: 12 start-page: 1 issue: 1 year: 2021 ident: 4160_CR6 publication-title: Nat. Commun. doi: 10.1038/s41467-020-20314-w – ident: 4160_CR10 doi: 10.1109/HPCA51647.2021.00026 – ident: 4160_CR11 doi: 10.1145/3295500.3356155 – volume: 10 issue: 4 year: 2020 ident: 4160_CR17 publication-title: Phys. Rev. X – volume: 13 start-page: 0206704 issue: 12 year: 2018 ident: 4160_CR9 publication-title: PLoS ONE doi: 10.1371/journal.pone.0206704 |
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