English

Quantum computational chemistry

Quantum Physics 2020-04-08 v3

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.

Keywords

Cite

@article{arxiv.1808.10402,
  title  = {Quantum computational chemistry},
  author = {Sam McArdle and Suguru Endo and Alan Aspuru-Guzik and Simon Benjamin and Xiao Yuan},
  journal= {arXiv preprint arXiv:1808.10402},
  year   = {2020}
}

Comments

Major updates: improvements to introduction and future work sections, added examples throughout, added additional references, streamlined sections on near-term approaches

R2 v1 2026-06-23T03:49:29.887Z