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

Simulating ultrafast quantum dissipation in molecular excited states is a strongly demanding computational task. Here, the authors combine tensor network simulation, entanglement renormalisation and machine learning to simulate linear vibronic models, and test the method by analysing singlet fission...

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Autores principales:	Florian A. Y. N. Schröder, David H. P. Turban, Andrew J. Musser, Nicholas D. M. Hine, Alex W. Chin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/d3bfe9f28a474dacaa1376b861424f7e
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spelling	oai:doaj.org-article:d3bfe9f28a474dacaa1376b861424f7e2021-12-02T14:39:36ZTensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation10.1038/s41467-019-09039-72041-1723https://doaj.org/article/d3bfe9f28a474dacaa1376b861424f7e2019-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-09039-7https://doaj.org/toc/2041-1723Simulating ultrafast quantum dissipation in molecular excited states is a strongly demanding computational task. Here, the authors combine tensor network simulation, entanglement renormalisation and machine learning to simulate linear vibronic models, and test the method by analysing singlet fission dynamics.Florian A. Y. N. SchröderDavid H. P. TurbanAndrew J. MusserNicholas D. M. HineAlex W. ChinNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-10 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Florian A. Y. N. Schröder David H. P. Turban Andrew J. Musser Nicholas D. M. Hine Alex W. Chin Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
description	Simulating ultrafast quantum dissipation in molecular excited states is a strongly demanding computational task. Here, the authors combine tensor network simulation, entanglement renormalisation and machine learning to simulate linear vibronic models, and test the method by analysing singlet fission dynamics.
format	article
author	Florian A. Y. N. Schröder David H. P. Turban Andrew J. Musser Nicholas D. M. Hine Alex W. Chin
author_facet	Florian A. Y. N. Schröder David H. P. Turban Andrew J. Musser Nicholas D. M. Hine Alex W. Chin
author_sort	Florian A. Y. N. Schröder
title	Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
title_short	Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
title_full	Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
title_fullStr	Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
title_full_unstemmed	Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
title_sort	tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/d3bfe9f28a474dacaa1376b861424f7e
work_keys_str_mv	AT florianaynschroder tensornetworksimulationofmultienvironmentalopenquantumdynamicsviamachinelearningandentanglementrenormalisation AT davidhpturban tensornetworksimulationofmultienvironmentalopenquantumdynamicsviamachinelearningandentanglementrenormalisation AT andrewjmusser tensornetworksimulationofmultienvironmentalopenquantumdynamicsviamachinelearningandentanglementrenormalisation AT nicholasdmhine tensornetworksimulationofmultienvironmentalopenquantumdynamicsviamachinelearningandentanglementrenormalisation AT alexwchin tensornetworksimulationofmultienvironmentalopenquantumdynamicsviamachinelearningandentanglementrenormalisation
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Tensor network simulation of multi-environmental open quantum dynamics via machine learning and entanglement renormalisation

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