Toward efficient quantum computation of molecular ground‐state energies

Abstract Variational quantum eigensolvers (VQEs) represent a promising approach to computing molecular ground states and energies on modern quantum computers. These approaches use a classical computer to optimize the parameters of a trial wave function, while the quantum computer simulates the energy by preparing and measuring a set of bitstring observations, referred to as shots, over which an expected value is computed. Although more shots improve the accuracy of the expected ground state, it also increases the simulation cost. Hence, we propose modifications to the standard Bayesian optimization algorithm to leverage few‐shot circuit observations to solve VQEs with fewer quantum resources. We demonstrate the effectiveness of our proposed approach, Bayesian optimization with priors on surface topology (BOPT), by comparing optimizers for molecular systems and demonstrate how current quantum hardware can aid in finding ground‐state energies.

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Publication Details

Journal
AIChE Journal
Published
2025-09-24
DOI
https://doi.org/10.1002/aic.18887
Citations
2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
4.96

Funders

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Toward efficient quantum computation of molecular ground‐state energies

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2 citations
AIChE Journal
Quantum Computing Algorithms and Architecture
4.96
article

Toward efficient quantum computation of molecular ground‐state energies

Farshud Sorourifar, David E. Bernal, Erik Gustafson, Nacer Eddine Belaloui, Joel A. Paulson, Diana Chamaki, Mohamed Taha Rouabah, Norm M. Tubman, Mohamed Messaoud Louamri
article en
2 citations

Abstract

Abstract Variational quantum eigensolvers (VQEs) represent a promising approach to computing molecular ground states and energies on modern quantum computers. These approaches use a classical computer to optimize the parameters of a trial wave function, while the quantum computer simulates the energy by preparing and measuring a set of bitstring observations, referred to as shots, over which an expected value is computed. Although more shots improve the accuracy of the expected ground state, it also increases the simulation cost. Hence, we propose modifications to the standard Bayesian optimization algorithm to leverage few‐shot circuit observations to solve VQEs with fewer quantum resources. We demonstrate the effectiveness of our proposed approach, Bayesian optimization with priors on surface topology (BOPT), by comparing optimizers for molecular systems and demonstrate how current quantum hardware can aid in finding ground‐state energies.

AIChE JournalVol. 71(12)
University Frères Mentouri Constantine 1 (DZ), Ames Research Center (US), Research Institute for Advanced Computer Science (US), University of Sciences and Technology Houari Boumediene (DZ), Purdue University West Lafayette (US), The Ohio State University (US), Columbia University (US)
National Science Foundation, U.S. Department of Energy, Purdue University, Advanced Scientific Computing Research
Openalex Percentile: Top 5%
Quantum Computing Algorithms and Architecture
4.96
DOIOpen Access PDFOpenAlex
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