Quantum algorithm for alchemical optimization in material design

TL;DR

This paper introduces a quantum algorithm that efficiently explores the vast chemical space for material design by representing candidate structures as superpositions and optimizing properties using quantum computing, demonstrating promising results in simulations and hardware.

Contribution

It presents a novel quantum algorithm for material design that scales favorably and combines electronic structure calculation with chemical space sampling.

Findings

Successful simulation of the algorithm's efficiency

Implementation on IBM Quantum hardware shows promising results

Potential for near-term quantum advantage in material discovery

Abstract

The development of tailored materials for specific applications is an active field of research in chemistry, material science and drug discovery. The number of possible molecules that can be obtained from a set of atomic species grow exponentially with the size of the system, limiting the efficiency of classical sampling algorithms. On the other hand, quantum computers can provide an efficient solution to the sampling of the chemical compound space for the optimization of a given molecular property. In this work we propose a quantum algorithm for addressing the material design problem with a favourable scaling. The core of this approach is the representation of the space of candidate structures as a linear superposition of all possible atomic compositions. The corresponding `alchemical' Hamiltonian drives then the optimization in both the atomic and electronic spaces leading to the selection of the best fitting molecule, which optimizes a given property of the system, e.g., the interaction with an external potential in drug design. The quantum advantage resides in the efficient calculation of the electronic structure properties together with the sampling of the exponentially large chemical compound space. We demonstrate both in simulations and in IBM Quantum hardware the efficiency of our scheme and highlight the results in a few test cases. These preliminary results can serve as a basis for the development of further material design quantum algorithms for near-term quantum computers.