A Case for Efficient and Scalable Tree-Based Quantum Circuit Simulator

Quantum computers can speed up computationally hard problems. However, to realize their full potential, we must mitigate qubit errors (from noise) by developing noise-aware algorithms, compilers, and architectures. Thus, simulating quantum programs on classical computers with different noise models is a de-facto tool that is used by researchers and practitioners. Unfortunately, for large quantum circuits, noisy simulators iteratively execute the same circuit across multiple trials (shots) – thereby incurring large performance overheads.

To address this, we propose a noisy simulation technique called Tree-Based Quantum Circuit Simulation (TQSim). TQSim exploits the reusability of the intermediate results during the noisy simulation and reduces computation. TQSim dynamically partitions a circuit into several subcircuits. It then reuses the intermediate results from these subcircuits during computation. As compared to a noisy Qulacs-based baseline simulator, TQSim achieves an average speedup of 2.51× across 48 different benchmark circuits. Additionally, across benchmarks, TQSim produces results with a normalized fidelity that is within 0.016 range of the baseline normalized fidelity. TQSim maintains the same speedup when going from single-node to multi-node simulation