Near-term quantum algorithm for computing molecular and materials properties based on recursive variational series methods

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is: how might we use imperfect near-term quantum computers to solve problems of practical value? We propose a quantum algorithm to estimate the properties of molecules using near-term quantum devices. The method is a recursive variational series estimation method, where we expand an operator of interest in terms of Chebyshev polynomials and evaluate each term in the expansion using a variational quantum algorithm. We test our method by computing the one-particle Green's function in the energy domain and the autocorrelation function in the time domain.

Automated summary

The study proposes a quantum algorithm to estimate the properties of molecules using near-term quantum devices. The method uses a recursive variational series estimation approach and evaluates each term in the expansion using a variational quantum algorithm. The algorithm is tested by computing the one-particle Green's function in the energy domain and the autocorrelation function in the time domain.