Quantum simulation of battery materials using ionic pseudopotentials

We introduce a quantum algorithm that uses pseudopotentials to reduce the cost of simulating periodic materials on a quantum computer. We address the challenge of incorporating the complexity of pseudopotentials into quantum simulations by developing highly-optimized compilation strategies for the qubitization of the Hamiltonian. This includes a linear combination of unitaries decomposition that leverages the form of separable pseudopotentials. We estimate the computational cost of applying our algorithm to simulating three lithium-excess cathode materials for batteries: lithium manganese oxide, lithium nickel-manganese oxide, and lithium manganese oxyfluoride. Our optimized compilation strategies result in a pseudopotential-based quantum algorithm with a total runtime four orders of magnitude lower than the previous state of the art for a fixed target accuracy.