X-ray absorption spectroscopy is a crucial experimental technique for elucidating the mechanisms of structural degradation in battery materials. However, extracting information from the measured spectrum is challenging without high-quality simulations. In this work, we propose simulating near-edge X-ray absorption spectra as a promising application for quantum computing. It is attractive due to the ultralocal nature of X-ray absorption that significantly reduces the sizes of problems to be simulated, and because of the classical hardness of simulating spectra. We describe three quantum algorithms to compute the X-ray absorption spectrum and provide their asymptotic cost. One of these is a Monte-Carlo based time-domain algorithm, which is cost-friendly to early fault-tolerant quantum computers. We then apply the framework to an industrially relevant example, a CAS(22e,18o) active space for an O-Mn cluster in a Li-excess battery cathode, showing that practically useful simulations could be obtained with much fewer qubits and gates than ground-state energy estimation of the same material.
@article{arxiv.2405.11015,
title = {Simulating X-ray absorption spectroscopy of battery materials on a quantum computer},
author = {Stepan Fomichev and Kasra Hejazi and Ignacio Loaiza and Modjtaba Shokrian Zini and Alain Delgado and Arne-Christian Voigt and Jonathan E. Mueller and Juan Miguel Arrazola},
journal= {arXiv preprint arXiv:2405.11015},
year = {2024}
}