Tensorized Pauli decomposition algorithm

Abstract

This paper introduces a novel general-purpose algorithm for Pauli decomposition that employs matrix slicing and addition rather than expensive matrix multiplication, significantly accelerating the decomposition of multi-qubit matrices. In a detailed complexity analysis, we show that the algorithm admits the best known worst-case scaling and more favorable runtimes for many practical examples. Numerical experiments are provided to validate the asymptotic speed-up already for small instance sizes, underscoring the algorithm's potential significance in the realm of quantum computing and quantum chemistry simulations.

This is the Accepted Manuscript version of an article accepted for publication in Phys. Scr.. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. This Accepted Manuscript is published under a CC BY licence. The Version of Record is available online at 10.1088/1402-4896/ad6499

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• Notes on Quantum Computing for Thermal Science
• Resource-efficient Quantum Algorithms for Selected Hamiltonian Subspace Diagonalization
• A variational quantum eigensolver tailored to multi-band tight-binding simulations of electronic structures