Quantum Chemistry with Quantum Computers and Neural Networks

Abstract

Quantum computers and neural networks promise to enhance computations of electronic structures. Here we discuss how they can be used separately and in synergy to calculate molecular ground state energies. First, we show that both quantum circuits and and neural networks can be used as variational ansatzes for ground state energies, each with its own advantages. By appending neural network post-processing to energy estimates generated with a quantum computer, we show that precision and resistance to decoherence noise of such estimates can be improved.