We introduce a simple algorithm that efficiently computes tensor products of Pauli matrices. This is done by tailoring the calculations to this specific case, which allows to avoid unnecessary calculations. The strength of this strategy is benchmarked against state-of-the-art techniques, showing a remarkable acceleration. As a side product, we provide an optimized method for one key calculus in quantum simulations: the Pauli basis decomposition of Hamiltonians.
Manuscript available at Quantum Inf Process 22, 449 (2023).
If you use PauliComposer in your work, thanks for your interest and please cite our corresponding manuscript as:
@article{paulicomposer2023,
title={PauliComposer: compute tensor products of Pauli matrices efficiently},
volume={22},
ISSN={1573-1332},
url={https://link.springer.com/10.1007/s11128-023-04204-w},
DOI={10.1007/s11128-023-04204-w},
number={12},
journal={Quantum Information Processing},
author={V. Romero, Sebastián and Santos-Suárez, Juan},
year={2023},
month=dec,
pages={449}
}