GraFeyn: Efficient Parallel Sparse Simulation of Quantum Circuits

Many circuit simulators use either a Schrodinger-based or Feynman-based approach, which have complementary strengths. Schrödinger-based simulators maintain a state vector by synchronously updating it after each gate (or group of gates), ensuring time efficiency at the cost of exponential space. In contrast, Feynman-based simulators use low space but require high time to compute the sum of exponentially many independent Feynman paths. Because they treat paths as independent, Feynman-based simulators miss opportunities to take advantage of sparsity from destructive interference. In this paper, we present a hybrid Schrödinger-Feynman technique which takes advantage of sparsity by selectively synchronizing Feynman paths. Our hybrid technique partitions the circuit into kernels (groups of gates) and uses Feynman simulation within each kernel. It then synchronizes across the kernels by using Schrödinger-style simulation. We parallelize our approach by representing the simulation as a graph, leveraging state-of-the-art parallel graph algorithms. By selecting kernels carefully, we show that our approach can simulate hundreds of qubits efficiently (in both time and space) on just a single multicore node. In certain “sparse” circuits, we are able to improve running times by multiple orders of magnitude.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.00132
Citations
2
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.98

Funders

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article

GraFeyn: Efficient Parallel Sparse Simulation of Quantum Circuits

Mike Rainey, Mingkuan Xu, Yongshan Ding, Umut A. Acar et al.
2 citations
Parallel Computing and Optimization Techniques
0.98
article

GraFeyn: Efficient Parallel Sparse Simulation of Quantum Circuits

Mike Rainey, Mingkuan Xu, Yongshan Ding, Umut A. Acar, Colin McDonald, Jatin Arora, Sam Westrick, Byeongjee Kang, Pengyu Liu
article en
2 citations

Abstract

Many circuit simulators use either a Schrodinger-based or Feynman-based approach, which have complementary strengths. Schrödinger-based simulators maintain a state vector by synchronously updating it after each gate (or group of gates), ensuring time efficiency at the cost of exponential space. In contrast, Feynman-based simulators use low space but require high time to compute the sum of exponentially many independent Feynman paths. Because they treat paths as independent, Feynman-based simulators miss opportunities to take advantage of sparsity from destructive interference. In this paper, we present a hybrid Schrödinger-Feynman technique which takes advantage of sparsity by selectively synchronizing Feynman paths. Our hybrid technique partitions the circuit into kernels (groups of gates) and uses Feynman simulation within each kernel. It then synchronizes across the kernels by using Schrödinger-style simulation. We parallelize our approach by representing the simulation as a graph, leveraging state-of-the-art parallel graph algorithms. By selecting kernels carefully, we show that our approach can simulate hundreds of qubits efficiently (in both time and space) on just a single multicore node. In certain “sparse” circuits, we are able to improve running times by multiple orders of magnitude.

Yale University (US), Carnegie Mellon University (US)
National Science Foundation
Openalex Percentile: Top 22%
Parallel Computing and Optimization Techniques
0.98
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