ArticleChemical science2021
Quantum algorithm for alchemical optimization in material design.
Article in Chemical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Quantum computing in surgery and urology - taking a quantum leap.Nature reviews. Urology · 2026Article
- Quantum Computing in Drug Discovery Techniques, Challenges, and Emerging Opportunities.Current drug discovery technologies · 2026Review
- Provable bounds for noise-free expectation values computed from noisy samples.Nature computational science · 2024Article
- Biology and medicine in the landscape of quantum advantages.Journal of the Royal Society, Interface · 2022Review
- Ab Initio Machine Learning in Chemical Compound Space.Chemical reviews · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of tailored materials for specific applications is an active field of research in chemistry, material science and drug discovery. The number of possible molecules obtainable from a set of atomic species grow exponentially with the size of the system, limiting the efficiency of classical sampling algorithms. On the other hand, quantum computers can provide an efficient solution to the sampling of the chemical compound space for the optimization of a given molecular property. In this work, we propose a quantum algorithm for addressing the material design problem with a favourable scaling. The core of this approach is the representation of the space of candidate structures as a linear superposition of all possible atomic compositions. The corresponding 'alchemical' Hamiltonian drives the optimization in both the atomic and electronic spaces leading to the selection of the best fitting molecule, which optimizes a given property of the system,
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Registered trials
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