Enabling Scalable VQE Simulation on Leading HPC Systems

Meng Wang; Fei Hua; Chenxu Liu; Nicholas Bauman; Karol Kowalski; Daniel Claudino; Travis Humble; Prashant Nair; Ang Li

doi:10.1145/3624062.3624221

Enabling Scalable VQE Simulation on Leading HPC Systems

Meng Wang, Fei Hua, Chenxu Liu, Nicholas Bauman, Karol Kowalski, Daniel Claudino, Travis Humble, Prashant Nair, Ang Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Large-scale simulations of quantum circuits pose significant challenges, especially in quantum chemistry, due to the number of qubits, circuit depth, and the number of circuits needed per problem. High-performance computing (HPC) systems offer massive computational capabilities that could help overcome these obstacles. We developed a high-performance quantum circuit simulator called NWQ-Sim, and demonstrated its capability to simulate large quantum chemistry problems on NERSC's Perlmutter supercomputer. Integrating NWQ-Sim with XACC, an open-source programming framework for quantum-classical applications, we have executed quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms for downfolded quantum chemistry systems at unprecedented scales. Our work demonstrates the potential of leveraging HPC resources and optimized simulators to advance quantum chemistry and other applications of near-term quantum devices. By scaling to larger qubit counts and circuit depths, high-performance simulators like NWQ-Sim will be critical for characterizing and validating quantum algorithms before their deployment on actual quantum hardware.

Original language	English
Title of host publication	Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023
Publisher	Association for Computing Machinery
Pages	1460-1467
Number of pages	8
ISBN (Electronic)	9798400707858
DOIs	https://doi.org/10.1145/3624062.3624221
State	Published - Nov 12 2023
Event	2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 - Denver, United States Duration: Nov 12 2023 → Nov 17 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023
Country/Territory	United States
City	Denver
Period	11/12/23 → 11/17/23

Funding

This material is based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231 using NERSC award ERCAP0023224 and ERCAP0023053. This material is also supported by the National Research Council Canada grant AQC 003 and by the Natural Sciences and Engineering Research Council of Canada (NSERC) [funding reference number RGPIN-2019-05059].

Keywords

Quantum computing
high-performance computing
hybrid quantum-classical computing
quantum algorithms
quantum chemistry
quantum simulation
variational algorithms

Access to Document

10.1145/3624062.3624221

Cite this

Wang, M., Hua, F., Liu, C., Bauman, N., Kowalski, K., Claudino, D., Humble, T., Nair, P., & Li, A. (2023). Enabling Scalable VQE Simulation on Leading HPC Systems. In Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 (pp. 1460-1467). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3624062.3624221

@inproceedings{eee5e436a8c94d9896dbf663a1e132b6,

title = "Enabling Scalable VQE Simulation on Leading HPC Systems",

abstract = "Large-scale simulations of quantum circuits pose significant challenges, especially in quantum chemistry, due to the number of qubits, circuit depth, and the number of circuits needed per problem. High-performance computing (HPC) systems offer massive computational capabilities that could help overcome these obstacles. We developed a high-performance quantum circuit simulator called NWQ-Sim, and demonstrated its capability to simulate large quantum chemistry problems on NERSC's Perlmutter supercomputer. Integrating NWQ-Sim with XACC, an open-source programming framework for quantum-classical applications, we have executed quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms for downfolded quantum chemistry systems at unprecedented scales. Our work demonstrates the potential of leveraging HPC resources and optimized simulators to advance quantum chemistry and other applications of near-term quantum devices. By scaling to larger qubit counts and circuit depths, high-performance simulators like NWQ-Sim will be critical for characterizing and validating quantum algorithms before their deployment on actual quantum hardware.",

keywords = "Quantum computing, high-performance computing, hybrid quantum-classical computing, quantum algorithms, quantum chemistry, quantum simulation, variational algorithms",

author = "Meng Wang and Fei Hua and Chenxu Liu and Nicholas Bauman and Karol Kowalski and Daniel Claudino and Travis Humble and Prashant Nair and Ang Li",

note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 ; Conference date: 12-11-2023 Through 17-11-2023",

year = "2023",

month = nov,

day = "12",

doi = "10.1145/3624062.3624221",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "1460--1467",

booktitle = "Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023",

}

Wang, M, Hua, F, Liu, C, Bauman, N, Kowalski, K, Claudino, D , Humble, T, Nair, P & Li, A 2023, Enabling Scalable VQE Simulation on Leading HPC Systems. in Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 1460-1467, 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023, Denver, United States, 11/12/23. https://doi.org/10.1145/3624062.3624221

Enabling Scalable VQE Simulation on Leading HPC Systems. / Wang, Meng; Hua, Fei; Liu, Chenxu et al.
Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. Association for Computing Machinery, 2023. p. 1460-1467 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Enabling Scalable VQE Simulation on Leading HPC Systems

AU - Wang, Meng

AU - Hua, Fei

AU - Liu, Chenxu

AU - Bauman, Nicholas

AU - Kowalski, Karol

AU - Claudino, Daniel

AU - Humble, Travis

AU - Nair, Prashant

AU - Li, Ang

PY - 2023/11/12

Y1 - 2023/11/12

N2 - Large-scale simulations of quantum circuits pose significant challenges, especially in quantum chemistry, due to the number of qubits, circuit depth, and the number of circuits needed per problem. High-performance computing (HPC) systems offer massive computational capabilities that could help overcome these obstacles. We developed a high-performance quantum circuit simulator called NWQ-Sim, and demonstrated its capability to simulate large quantum chemistry problems on NERSC's Perlmutter supercomputer. Integrating NWQ-Sim with XACC, an open-source programming framework for quantum-classical applications, we have executed quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms for downfolded quantum chemistry systems at unprecedented scales. Our work demonstrates the potential of leveraging HPC resources and optimized simulators to advance quantum chemistry and other applications of near-term quantum devices. By scaling to larger qubit counts and circuit depths, high-performance simulators like NWQ-Sim will be critical for characterizing and validating quantum algorithms before their deployment on actual quantum hardware.

AB - Large-scale simulations of quantum circuits pose significant challenges, especially in quantum chemistry, due to the number of qubits, circuit depth, and the number of circuits needed per problem. High-performance computing (HPC) systems offer massive computational capabilities that could help overcome these obstacles. We developed a high-performance quantum circuit simulator called NWQ-Sim, and demonstrated its capability to simulate large quantum chemistry problems on NERSC's Perlmutter supercomputer. Integrating NWQ-Sim with XACC, an open-source programming framework for quantum-classical applications, we have executed quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms for downfolded quantum chemistry systems at unprecedented scales. Our work demonstrates the potential of leveraging HPC resources and optimized simulators to advance quantum chemistry and other applications of near-term quantum devices. By scaling to larger qubit counts and circuit depths, high-performance simulators like NWQ-Sim will be critical for characterizing and validating quantum algorithms before their deployment on actual quantum hardware.

KW - Quantum computing

KW - high-performance computing

KW - hybrid quantum-classical computing

KW - quantum algorithms

KW - quantum chemistry

KW - quantum simulation

KW - variational algorithms

UR - http://www.scopus.com/inward/record.url?scp=85178115958&partnerID=8YFLogxK

U2 - 10.1145/3624062.3624221

DO - 10.1145/3624062.3624221

M3 - Conference contribution

AN - SCOPUS:85178115958

T3 - ACM International Conference Proceeding Series

SP - 1460

EP - 1467

BT - Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023

PB - Association for Computing Machinery

T2 - 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023

Y2 - 12 November 2023 through 17 November 2023

ER -

Wang M, Hua F, Liu C, Bauman N, Kowalski K, Claudino D et al. Enabling Scalable VQE Simulation on Leading HPC Systems. In Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. Association for Computing Machinery. 2023. p. 1460-1467. (ACM International Conference Proceeding Series). doi: 10.1145/3624062.3624221

Enabling Scalable VQE Simulation on Leading HPC Systems

Abstract

Publication series

Conference

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this