Simulating X-ray absorption spectroscopy of battery materials on a quantum computer

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...

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Bibliographic Details
Published in:arXiv.org 2024-05
Main Authors: Fomichev, Stepan, Hejazi, Kasra, Loaiza, Ignacio, Modjtaba Shokrian Zini, Delgado, Alain, Arne-Christian Voigt, Mueller, Jonathan E, Juan Miguel Arrazola
Format: Article
Language:English
Subjects:
Absorption spectra
Absorption spectroscopy
Algorithms
Cathodes
Fault tolerance
Quantum computers
Quantum computing
Qubits (quantum computing)
Spectrum analysis
X ray absorption
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Summary: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.
ISSN:2331-8422