TY - GEN
T1 - CutQC
T2 - 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2021
AU - Tang, Wei
AU - Tomesh, Teague
AU - Suchara, Martin
AU - Larson, Jeffrey
AU - Martonosi, Margaret
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/4/19
Y1 - 2021/4/19
N2 - Quantum computing (QC) is a new paradigm offering the potential of exponential speedups over classical computing for certain computational problems. Each additional qubit doubles the size of the computational state space available to a QC algorithm. This exponential scaling underlies QC's power, but today's Noisy Intermediate-Scale Quantum (NISQ) devices face significant engineering challenges in scalability. The set of quantum circuits that can be reliably run on NISQ devices is limited by their noisy operations and low qubit counts. This paper introduces CutQC, a scalable hybrid computing approach that combines classical computers and quantum computers to enable evaluation of quantum circuits that cannot be run on classical or quantum computers alone. CutQC cuts large quantum circuits into smaller subcircuits, allowing them to be executed on smaller quantum devices. Classical postprocessing can then reconstruct the output of the original circuit. This approach offers significant runtime speedup compared with the only viable current alternative-purely classical simulations- A nd demonstrates evaluation of quantum circuits that are larger than the limit of QC or classical simulation. Furthermore, in real-system runs, CutQC achieves much higher quantum circuit evaluation fidelity using small prototype quantum computers than the state-of-the-art large NISQ devices achieve. Overall, this hybrid approach allows users to leverage classical and quantum computing resources to evaluate quantum programs far beyond the reach of either one alone.
AB - Quantum computing (QC) is a new paradigm offering the potential of exponential speedups over classical computing for certain computational problems. Each additional qubit doubles the size of the computational state space available to a QC algorithm. This exponential scaling underlies QC's power, but today's Noisy Intermediate-Scale Quantum (NISQ) devices face significant engineering challenges in scalability. The set of quantum circuits that can be reliably run on NISQ devices is limited by their noisy operations and low qubit counts. This paper introduces CutQC, a scalable hybrid computing approach that combines classical computers and quantum computers to enable evaluation of quantum circuits that cannot be run on classical or quantum computers alone. CutQC cuts large quantum circuits into smaller subcircuits, allowing them to be executed on smaller quantum devices. Classical postprocessing can then reconstruct the output of the original circuit. This approach offers significant runtime speedup compared with the only viable current alternative-purely classical simulations- A nd demonstrates evaluation of quantum circuits that are larger than the limit of QC or classical simulation. Furthermore, in real-system runs, CutQC achieves much higher quantum circuit evaluation fidelity using small prototype quantum computers than the state-of-the-art large NISQ devices achieve. Overall, this hybrid approach allows users to leverage classical and quantum computing resources to evaluate quantum programs far beyond the reach of either one alone.
KW - Hybrid Computing
KW - Quantum Circuit Cutting
KW - Quantum Computing (QC)
UR - http://www.scopus.com/inward/record.url?scp=85102120228&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102120228&partnerID=8YFLogxK
U2 - 10.1145/3445814.3446758
DO - 10.1145/3445814.3446758
M3 - Conference contribution
AN - SCOPUS:85102120228
T3 - International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
SP - 473
EP - 486
BT - Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2021
PB - Association for Computing Machinery
Y2 - 19 April 2021 through 23 April 2021
ER -