Simulating Quantum Circuits by Model Counting
<|reference_start|>Simulating Quantum Circuits by Model Counting: Quantum circuit compilation comprises many computationally hard reasoning tasks that nonetheless lie inside #$\mathbf{P}$ and its decision counterpart in $\mathbf{PP}$. The classical simulation of general quantum circuits is a core example. We show for the first time that a strong simulation of universal quantum circuits can be efficiently tackled through weighted model counting by providing a linear encoding of Clifford+T circuits. To achieve this, we exploit the stabilizer formalism by Knill, Gottesmann, and Aaronson and the fact that stabilizer states form a basis for density operators. With an open-source simulator implementation, we demonstrate empirically that model counting often outperforms state-of-the-art simulation techniques based on the ZX calculus and decision diagrams. Our work paves the way to apply the existing array of powerful classical reasoning tools to realize efficient quantum circuit compilation; one of the obstacles on the road towards quantum supremacy.<|reference_end|>
@article{mei2024simulating,
    title={Simulating Quantum Circuits by Model Counting},
    author={Jingyi Mei, Marcello Bonsangue and Alfons Laarman},
    journal={arXiv preprint arXiv:2403.07197},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.07197},
    primaryClass={quant-ph cs.LO}
}