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May 6, 2026The Journal of Chemical Physics

Integrating quantum neural networks with the variational quantum eigensolver to calculate nonadiabatic coupling vectors

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Authors

SZS F ZhangZLZhen LiuZLZhenyu Li

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Overview

The integration of quantum neural networks and variational quantum eigensolvers predicts nonadiabatic coupling vectors, suggesting a unified approach for electronic structure calculations.

Key Points

  • This research aims to enhance the prediction of nonadiabatic coupling vectors using integrated quantum technologies.
  • Utilized quantum neural networks to learn parameters from variational quantum eigensolver wavefunctions.
  • Implemented a bootstrap optimization procedure to initialize model parameters by scanning potential energy surfaces.
  • Calculated nonadiabatic coupling vectors directly from the optimized wavefunctions.
  • Successfully reduced the localized value and sign problems in NACV calculations.
  • Achieved efficient determination of potential energy surfaces alongside nonadiabatic coupling vectors.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69faa2e204f884e66b5336ffhttps://doi.org/10.1063/5.0319519
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