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Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation

Author

Listed:
  • Florian A. Y. N. Schröder

    (University of Cambridge)

  • David H. P. Turban

    (University of Cambridge)

  • Andrew J. Musser

    (University of Sheffield)

  • Nicholas D. M. Hine

    (University of Warwick)

  • Alex W. Chin

    (CNRS & Institut des NanoSciences de Paris, Sorbonne Université)

Abstract

The simulation of open quantum dynamics is a critical tool for understanding how the non-classical properties of matter might be functionalised in future devices. However, unlocking the enormous potential of molecular quantum processes is highly challenging due to the very strong and non-Markovian coupling of ‘environmental’ molecular vibrations to the electronic ‘system’ degrees of freedom. Here, we present an advanced but general computational strategy that allows tensor network methods to effectively compute the non-perturbative, real-time dynamics of exponentially large vibronic wave functions of real molecules. We demonstrate how ab initio modelling, machine learning and entanglement analysis can enable simulations which provide real-time insight and direct visualisation of dissipative photophysics, and illustrate this with an example based on the ultrafast process known as singlet fission.

Suggested Citation

  • Florian A. Y. N. Schröder & David H. P. Turban & Andrew J. Musser & Nicholas D. M. Hine & Alex W. Chin, 2019. "Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09039-7
    DOI: 10.1038/s41467-019-09039-7
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    Cited by:

    1. Wei-Ming Li & Shi-Ju Ran, 2022. "Non-Parametric Semi-Supervised Learning in Many-Body Hilbert Space with Rescaled Logarithmic Fidelity," Mathematics, MDPI, vol. 10(6), pages 1-15, March.
    2. Yuanheng Wang & Jiajun Ren & Zhigang Shuai, 2023. "Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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