Quantum computational chemistry

TL;DR

Quantum computational chemistry explores how quantum computing can address complex chemical problems, aiming to enable scientific breakthroughs and new compound design, despite current hardware limitations.

Contribution

This paper provides a comprehensive introduction and review of quantum computational chemistry, focusing on recent developments and methods for near-term quantum applications.

Findings

Mapping chemical problems onto quantum computers is feasible with current methods.

Quantum algorithms can potentially solve classically intractable chemistry problems.

The field is rapidly evolving with promising approaches for resource-efficient quantum computations.

Abstract

One of the most promising suggested applications of quantum computing is solving classically intractable chemistry problems. This may help to answer unresolved questions about phenomena like: high temperature superconductivity, solid-state physics, transition metal catalysis, or certain biochemical reactions. In turn, this increased understanding may help us to refine, and perhaps even one day design, new compounds of scientific and industrial importance. However, building a sufficiently large quantum computer will be a difficult scientific challenge. As a result, developments that enable these problems to be tackled with fewer quantum resources should be considered very important. Driven by this potential utility, quantum computational chemistry is rapidly emerging as an interdisciplinary field requiring knowledge of both quantum computing and computational chemistry. This review provides a comprehensive introduction to both computational chemistry and quantum computing, bridging the current knowledge gap. We review the major developments in this area, with a particular focus on near-term quantum computation. Illustrations of key methods are provided, explicitly demonstrating how to map chemical problems onto a quantum computer, and solve them. We conclude with an outlook for this nascent field.