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DiaQ: Efficient State-Vector Quantum Simulation

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arxiv 2405.01250 v1 pith:AVPEYREK submitted 2024-04-30 quant-ph cs.DCcs.DS

classification quant-phcs.DCcs.DS
keywords quantumdiaqefficientsimulationsimulationssparsitycircuitsdevelopment
verification ladder T0 review T1 audit T2 compute T3 formal

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In the current era of Noisy Intermediate Scale Quantum (NISQ) computing, efficient digital simulation of quantum systems holds significant importance for quantum algorithm development, verification and validation. However, analysis of sparsity within these simulations remains largely unexplored. In this paper, we present a novel observation regarding the prevalent sparsity patterns inherent in quantum circuits. We introduce DiaQ, a new sparse matrix format tailored to exploit this quantum-specific sparsity, thereby enhancing simulation performance. Our contribution extends to the development of libdiaq, a numerical library implemented in C++ with OpenMP for multi-core acceleration and SIMD vectorization, featuring essential mathematical kernels for digital quantum simulations. Furthermore, we integrate DiaQ with SV-Sim, a state vector simulator, yielding substantial performance improvements across various quantum circuits (e.g., ~26.67% for GHZ-28 and ~32.72% for QFT-29 with multi-core parallelization and SIMD vectorization on Frontier). Evaluations conducted on benchmarks from SupermarQ and QASMBench demonstrate that DiaQ represents a significant step towards achieving highly efficient quantum simulations.

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  1. Harnessing CUDA-Q's MPS for Tensor Network Simulations of Large-Scale Quantum Circuits

    quant-ph 2025-01 conditional novelty 4.0 of 10

    MPS simulation in CUDA-Q extends single-GPU quantum circuit simulation from 33 qubits (state vector) to 60 to 90 qubits for the tested circuits, with linear or power-law runtime scaling.

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