Quantum algorithm for simulating resonant inelastic X-ray scattering in battery materials

TL;DR

This paper introduces a quantum algorithm leveraging quantum phase estimation and signal processing to simulate RIXS spectra in battery materials, aiding interpretation of experimental data.

Contribution

It presents a novel quantum algorithm for simulating RIXS spectra of molecular clusters, including resource estimates for complex active spaces.

Findings

Resource estimation for 20-orbital active space: 2.0×10^10 Toffoli gates.

Algorithm successfully models RIXS spectra for a model cluster.

Uses PennyLane platform for simulation and resource analysis.

Abstract

Resonant inelastic X-ray scattering (RIXS) is the workhorse experimental technique for probing the structural degradation of higher-capacity cathode materials. However, the interpretation of experimental spectra is challenging due to the lack of accurate simulations. In this work, we propose a quantum algorithm for simulating the RIXS spectrum of molecular clusters hypothesized to form in Li-excess cathodes. The algorithm uses quantum phase estimation to sample the spectrum from a state encoding the scattering transition amplitudes of the cluster valence excitations. We prepare this state in the quantum computer using a block-encoding of the dipole operator and quantum signal processing to implement the Green's function propagator over intermediate core-excited states. To showcase the algorithm, we use a model cluster proposed in recent experimental works consisting of an oxygen dimer bonded to a manganese atom. Using the PennyLane software platform, we report resource estimation for simulating RIXS spectra for chemically motivated active spaces of increasing sizes. For a classically challenging active space with 20 orbitals, the algorithm requires $2.0 \times 10^{10}$ Toffoli gates and $414$ logical qubits.