Using Variational Eigensolvers on Low-End Hardware to Find the Ground State Energy of Simple Molecules

TL;DR

This paper explores the use of variational quantum eigensolvers on low-end hardware to accurately compute the ground state energies of simple molecules, comparing different optimization strategies for efficiency and accuracy.

Contribution

It evaluates the performance of various optimizers in variational quantum eigensolvers on low-end hardware for molecular energy calculations.

Findings

Certain optimizers achieved high accuracy with low computational cost

Variational quantum eigensolvers are feasible on low-end hardware for simple molecules

Optimization strategy significantly impacts the efficiency and accuracy of quantum eigensolvers

Abstract

Key properties of physical systems can be described by the eigenvalues of matrices that represent the system. Computational algorithms that determine the eigenvalues of these matrices exist, but they generally suffer from a loss of performance as the matrix grows in size. This process can be expanded to quantum computation to find the eigenvalues with better performance than the classical algorithms. One application of such an eigenvalue solver is to determine energy levels of a molecule given a matrix representation of its Hamiltonian using the variational principle. Using a variational quantum eigensolver, we determine the ground state energies of different molecules. We focus on the choice of optimization strategy for a Qiskit simulator on low-end hardware. The benefits of several different optimizers were weighed in terms of accuracy in comparison to an analytic classical solution as well as code efficiency.