Accelerating Simulation of Quantum Circuits under Noise via Computational Reuse

TL;DR

This paper introduces TQSim, a novel noisy quantum circuit simulation method that leverages intermediate result reuse to significantly accelerate simulations on HPC systems, aiding noise-aware quantum computing research.

Contribution

TQSim is a new simulation technique that dynamically partitions circuits and reuses intermediate results, achieving up to 3.89x speedup over existing methods.

Findings

TQSim achieves up to 3.89x speedup compared to baseline.

It maintains tight fidelity bounds during simulation.

Designed for efficient multi-node HPC setups.

Abstract

To realize the full potential of quantum computers, we must mitigate qubit errors by developing noise-aware algorithms, compilers, and architectures. Thus, simulating quantum programs on high-performance computing (HPC) systems with different noise models is a de facto tool researchers use. Unfortunately, noisy simulators iteratively execute a similar circuit for thousands of trials, thereby incurring significant performance overheads. To address this, we propose a noisy simulation technique called Tree-Based Quantum Circuit Simulation (TQSim). TQSim exploits the reusability of intermediate results during the noisy simulation, reducing computation. TQSim dynamically partitions a circuit into several subcircuits. It then reuses the intermediate results from these subcircuits during computation. Compared to a noisy Qulacs-based baseline simulator, TQSim achieves a speedup of up to 3.89x for noisy simulations. TQSim is designed to be efficient with multi-node setups while also maintaining tight fidelity bounds.