  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.
