Electronic Structure Simulations for Batteries and Fuel Cells Using a Quantum Computer

One of the original and most promising applications of quantum computing is the simulation of a wide variety of processes in Physics and Chemistry with relevant industrial and scientific applications. Until now, all the classical algorithms that simulate the electronic and vibrational structure of atoms and molecules are severely restricted by the exponential growth in computational resources that are required to accommodate large chemical problems. In contrast, the quantum mechanical foundations of quantum processors provide a novel framework by which the correspondence between chemical orbitals and physical qubits can be exploited to develop quantum algorithms that may surpass their classical counterparts and tackle demanding problems that would be otherwise

impossible to solve [1]. In the context of generating, transferring and storing energy, an accurate description of challenging molecular structures is vital for the advancement of these technologies, such as the development of accurate, multi-scale simulations of batteries or the modeling of the interaction between molecules and surfaces, central to the optimal operation of fuel cells.

In this work, we have implemented and evaluated the performance of a variety of hybrid quantum algorithms for the calculation of electronic structure that employ a synergy between classical optimization and quantum computation. We present the results of our simulations of relevant molecules like LiH and H2O on the IBM System One quantum computer, where state-of-the-art techniques of error mitigation have been employed. We focus on a class of hybrid algorithms that leverage additional measurements on the quantum processor without an increase in the complexity of the quantum circuits involved in the calculation, such as the Virtual Quantum Subspace Expansion method [2] that includes corrections to the ground state from virtual excitations. Finally, we investigate techniques like Entanglement Forging [3] that exploit partitions of the initial problem into strongly correlated sectors in order to achieve efficient quantum simulations of challenging systems like water.

[1] McArdle, S. et al. Rev. Mod. Phys., 92, 015003 (2020)

[2] Takeshita, T. et al. Phys. Rev. X, 10, 011004 (2020)

[3] Eddins, A. et al. arXiv:2104.10220 (2021)