Quantum Simulation of Electron Energy Loss Spectroscopy for Battery Materials

• URL: http://arxiv.org/abs/2508.15935v1
• Date: Thu, 21 Aug 2025 20:01:16 GMT
• Title: Quantum Simulation of Electron Energy Loss Spectroscopy for Battery Materials
• Authors: Alexander Kunitsa, Diksha Dhawan, Stepan Fomichev, Juan Miguel Arrazola, Minghao Zhang, Torin F. Stetina,
• Abstract summary: We present a quantum algorithm and an end-to-end simulation framework to compute the dynamic structure factor (DSF)<n>We apply this approach to the simulation of electron energy loss spectroscopy (EELS) in the core-level electronic excitation regime.
• Score: 38.065424255210765
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The dynamic structure factor (DSF) is a central quantity for interpreting a vast array of inelastic scattering experiments in chemistry and materials science, but its accurate simulation is a considerable challenge for classical computational methods. In this work, we present a quantum algorithm and an end-to-end simulation framework to compute the DSF, providing a general approach for simulating momentum-resolved spectroscopies. We apply this approach to the simulation of electron energy loss spectroscopy (EELS) in the core-level electronic excitation regime, a spectroscopic technique offering sub-nanometer spatial resolution and capable of resolving element-specific information, crucial for analyzing battery materials. We derive a quantum algorithm for computing the DSF for EELS by evaluating the off-diagonal terms of the time-domain Green's function, enabling the simulation of momentum-resolved spectroscopies. To showcase the algorithm, we study the oxygen K-edge EELS spectrum of lithium manganese oxide ($Li_2MnO_3$), a prototypical cathode material for investigating the mechanisms of oxygen redox in battery materials. For a representative model of an oxygen-centered cluster of $Li_2MnO_3$ with an active space of 18 active orbitals, the algorithm requires a circuit depth of $3.25\times10^{8}$ T gates, 100 logical qubits, and roughly $10^4$ shots.

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