Toward Accurate Post-Born-Oppenheimer Molecular Simulations on Quantum Computers: An Adaptive Variational Eigensolver with Nuclear-Electronic Frozen Natural Orbitals.


Journal

Journal of chemical theory and computation
ISSN: 1549-9626
Titre abrégé: J Chem Theory Comput
Pays: United States
ID NLM: 101232704

Informations de publication

Date de publication:
11 Dec 2023
Historique:
medline: 12 12 2023
pubmed: 12 12 2023
entrez: 11 12 2023
Statut: aheadofprint

Résumé

Nuclear quantum effects such as zero-point energy and hydrogen tunneling play a central role in many biological and chemical processes. The nuclear-electronic orbital (NEO) approach captures these effects by treating selected nuclei quantum mechanically on the same footing as electrons. On classical computers, the resources required for an exact solution of NEO-based models grow exponentially with system size. By contrast, quantum computers offer a means of solving this problem with polynomial scaling. However, due to the limitations of current quantum devices, NEO simulations are confined to the smallest systems described by minimal basis sets, whereas realistic simulations beyond the Born-Oppenheimer approximation require more sophisticated basis sets. For this purpose, we herein extend a hardware-efficient ADAPT-VQE method to the NEO framework in the frozen natural orbital (FNO) basis. We demonstrate on H

Identifiants

pubmed: 38081802
doi: 10.1021/acs.jctc.3c01091
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Anton Nykänen (A)

Algorithmiq Ltd., Kanavakatu 3C, Helsinki FI-00160, Finland.

Aaron Miller (A)

Algorithmiq Ltd., Kanavakatu 3C, Helsinki FI-00160, Finland.
School of Physics, Trinity College Dublin, College Green Dublin 2, Ireland.

Walter Talarico (W)

Algorithmiq Ltd., Kanavakatu 3C, Helsinki FI-00160, Finland.
Department of Applied Physics, QTF Centre of Excellence, Center for Quantum Engineering, Aalto University School of Science, Aalto FIN-00076, Finland.

Stefan Knecht (S)

Algorithmiq Ltd., Kanavakatu 3C, Helsinki FI-00160, Finland.
ETH Zürich, Department of Chemistry and Applied Life Sciences Vladimir-Prelog-Weg 1-5/10, Zürich 8093, Switzerland.

Arseny Kovyrshin (A)

Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca Gothenburg, Pepparedsleden 1, Molndal SE-431 83, Sweden.

Mårten Skogh (M)

Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca Gothenburg, Pepparedsleden 1, Molndal SE-431 83, Sweden.
Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Gothenburg 412 96, Sweden.

Lars Tornberg (L)

Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca Gothenburg, Pepparedsleden 1, Molndal SE-431 83, Sweden.

Anders Broo (A)

Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca Gothenburg, Pepparedsleden 1, Molndal SE-431 83, Sweden.

Stefano Mensa (S)

The Hartree Centre, STFC, Sci-Tech Daresbury, Warrington WA4 4AD, U.K.

Benjamin C B Symons (BCB)

The Hartree Centre, STFC, Sci-Tech Daresbury, Warrington WA4 4AD, U.K.

Emre Sahin (E)

The Hartree Centre, STFC, Sci-Tech Daresbury, Warrington WA4 4AD, U.K.

Jason Crain (J)

IBM Research Europe, Hartree Centre STFC Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, U.K.
Department of Biochemistry, University of Oxford, Oxford OX1 3QU, U.K.

Ivano Tavernelli (I)

IBM Quantum, IBM Research─Zürich, Rüschlikon 8803, Switzerland.

Fabijan Pavošević (F)

Algorithmiq Ltd., Kanavakatu 3C, Helsinki FI-00160, Finland.

Classifications MeSH