# DiaQ: Efficient State-Vector Quantum Simulation

arXiv: https://arxiv.org/abs/2405.01250 · HTML: https://mlsanity.com/paper/2405.01250/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Apr 2024.

## Built on by (most cited first, 1 of 1)

- [Symbolic Analysis of Grover Search Algorithm via Chain-of-Thought Reasoning and Quantum-Native Tokenization](https://mlsanity.com/paper/2505.04880/) (2025)

## Abstract (arXiv)

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.