Evidence map›Paper›PMID 39703417›Full record

ArticleChemical science2025

SHARC meets TEQUILA: mixed quantum-classical dynamics on a quantum computer using a hybrid quantum-classical algorithm.

Eduarda Sangiogo Gil, Markus Oppel, Jakob S Kottmann, Leticia González

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Article in Chemical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Eduarda Sangiogo GilFaculty of Chemistry, Institute of Theoretical Chemistry, Universität Wien A-1090 Vienna Austria eduarda.sangiogo.gil@univie.ac.at leticia.gonzalez@univie.ac.at.ORCID https://orcid.org/0000-0002-0945-2906
Markus OppelFaculty of Chemistry, Institute of Theoretical Chemistry, Universität Wien A-1090 Vienna Austria eduarda.sangiogo.gil@univie.ac.at leticia.gonzalez@univie.ac.at.ORCID https://orcid.org/0000-0001-6363-2310
Jakob S KottmannInstitute for Computer Science, Center for Advanced Analytics and Predictive Sciences, Universität Augsburg Augsburg Germany.
Leticia GonzálezFaculty of Chemistry, Institute of Theoretical Chemistry, Universität Wien A-1090 Vienna Austria eduarda.sangiogo.gil@univie.ac.at leticia.gonzalez@univie.ac.at.ORCID https://orcid.org/0000-0001-5112-794X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent developments in quantum computing are highly promising, particularly in the realm of quantum chemistry. Due to the noisy nature of currently available quantum hardware, hybrid quantum-classical algorithms have emerged as a reliable option for near-term simulations. Mixed quantum-classical dynamics methods effectively capture nonadiabatic effects by integrating classical nuclear dynamics with quantum chemical computations of the electronic properties. However, these methods face challenges due to the high computational cost of the quantum chemistry part. To mitigate the computational demand, we propose a method where the required electronic properties are computed through a hybrid quantum-classical approach that combines classical and quantum hardware. This framework employs the variational quantum eigensolver and variational quantum deflation algorithms to obtain ground and excited state energies, gradients, nonadiabatic coupling vectors, and transition dipole moments. These quantities are used to propagate the nonadiabatic molecular dynamics using the Tully's fewest switches surface hopping method, although the implementation is also compatible with other molecular dynamics approaches. The approach, implemented by integrating the molecular dynamics program package SHARC with the TEQUILA quantum computing framework, is validated by studying the

Identifiers

PMID39703417
PMCPMC11653199

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.