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Quantum chemistry

Computational chemistry seeks to use the rules of quantum mechanics to predict the physical properties and behavior of atoms, molecules, and materials. Despite the apparent exponential cost of exact classical methods for this task, scientists have made incredible progress over the last century via increasingly sophisticated approximate methods. As a result, computational chemistry is now a core part of the analyses of chemistry experiments, the pharmaceutical drug discovery pipeline, and the optimization of materials for catalysts and batteries. Two of the most widely performed calculations are the computation of the electronic structure and the vibrational structure of chemical systems. Given the inherently quantum mechanical nature of these problems, it follows that a number of quantum algorithms have been proposed for computational chemistry [1]. In this section, we focus on the electronic structure problem for molecules and materials, as well as the vibrational structure problem. For further reviews of quantum computing for chemistry, we refer readers to [2, 3, 4, 5].

Bibliography

  1. Alán Aspuru-Guzik, Anthony D Dutoi, Peter J Love, and Martin Head-Gordon. Simulated quantum computation of molecular energies. Science, 309(5741):1704–1707, 2005. arXiv: https://arxiv.org/abs/0604193. doi:10.1126/science.1113479.

  2. Sam McArdle, Suguru Endo, Alán Aspuru-Guzik, Simon C. Benjamin, and Xiao Yuan. Quantum computational chemistry. Reviews of Modern Physics, 92:015003, 3 2020. arXiv: https://arxiv.org/abs/1808.10402. URL: https://link.aps.org/doi/10.1103/RevModPhys.92.015003, doi:10.1103/RevModPhys.92.015003.

  3. Yudong Cao, Jonathan Romero, Jonathan P. Olson, Matthias Degroote, Peter D. Johnson, Mária Kieferová, Ian D. Kivlichan, Tim Menke, Borja Peropadre, Nicolas P. D. Sawaya, Sukin Sim, Libor Veis, and Alán Aspuru-Guzik. Quantum chemistry in the age of quantum computing. Chemical Reviews, 2019. arXiv: https://arxiv.org/abs/1812.09976. arXiv:1812.09976, doi:10.1021/acs.chemrev.8b00803.

  4. Bela Bauer, Sergey Bravyi, Mario Motta, and Garnet Kin-Lic Chan. Quantum algorithms for quantum chemistry and quantum materials science. Chemical Reviews, 120(22):12685–12717, 2020. arXiv: https://arxiv.org/abs/2001.03685. doi:10.1021/acs.chemrev.9b00829.

  5. Mario Motta and Julia E. Rice. Emerging quantum computing algorithms for quantum chemistry. WIREs Molecular Computational Science, 12(3):e1580, 2022. arXiv: https://arxiv.org/abs/2109.02873. URL: https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/wcms.1580, arXiv:https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wcms.1580, doi:https://doi.org/10.1002/wcms.1580.