Towards Battery Simulations on a Quantum Computer using Quantum Embedding

Abstract

Advances in quantum computing hold the potential to revolutionize the simulation of complex materials, including those critical for next-generation batteries. However, the complexity of typical battery materials is still prohibitive for exact simulations on current or near-term quantum hardware. One promising approach is the use of quantum embedding techniques, which enable the treatment of correlated electronic states in large systems by partitioning them into manageable subproblems. We explore the application of Density Matrix Embedding Theory (DMET) [1,2] as a quantum embedding method to bridge classical and quantum computational resources [3]. Within DMET, few correlated degrees of freedom can be solved on the quantum computer, while the remaining part is solved with classical methodology, self-consistently connected to the quantum part. This approach paves the way for real-world problems from battery simulation to profit from near-term quantum computers. Literature: [1] Knizia and Chan, Phys. Rev. Lett. 109, 186404 (2012) [2] Wouters et al., J. Chem. Theory Comput. 12, 2706 (2016) [3] Cao et al., npj Comput. Mater. 9, 78 (2023)