Variational ansatz-based quantum simulation of imaginary time evolution

TL;DR

This paper introduces a hybrid quantum algorithm for simulating imaginary time evolution, enabling efficient ground-state energy calculations and applications in optimization and machine learning on near-term quantum devices.

Contribution

It presents a variational approach for imaginary time evolution that is compatible with current quantum hardware, addressing the non-unitary challenge.

Findings

Successfully computed ground states of molecular systems

Algorithm is suitable for error mitigation on shallow circuits

Applicable to optimization and machine learning tasks

Abstract

Imaginary time evolution is a powerful tool for studying quantum systems. While it is possible to simulate with a classical computer, the time and memory requirements generally scale exponentially with the system size. Conversely, quantum computers can efficiently simulate quantum systems, but not non-unitary imaginary time evolution. We propose a variational algorithm for simulating imaginary time evolution on a hybrid quantum computer. We use this algorithm to find the ground-state energy of many-particle systems; specifically molecular hydrogen and lithium hydride, finding the ground state with high probability. Our method can also be applied to general optimisation problems and quantum machine learning. As our algorithm is hybrid, suitable for error mitigation and can exploit shallow quantum circuits, it can be implemented with current quantum computers.