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DFT-inspired methods for quantum thermodynamics

In the framework of quantum thermodynamics, we propose a method to quantitatively describe thermodynamic quantities for out-of-equilibrium interacting many-body systems. The method is articulated in various approximation protocols which allow to achieve increasing levels of accuracy, it is relativel...

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Detalles Bibliográficos
Autores principales: Herrera, Marcela, Serra, Roberto M., D’Amico, Irene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498538/
https://www.ncbi.nlm.nih.gov/pubmed/28680064
http://dx.doi.org/10.1038/s41598-017-04478-y
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author Herrera, Marcela
Serra, Roberto M.
D’Amico, Irene
author_facet Herrera, Marcela
Serra, Roberto M.
D’Amico, Irene
author_sort Herrera, Marcela
collection PubMed
description In the framework of quantum thermodynamics, we propose a method to quantitatively describe thermodynamic quantities for out-of-equilibrium interacting many-body systems. The method is articulated in various approximation protocols which allow to achieve increasing levels of accuracy, it is relatively simple to implement even for medium and large number of interactive particles, and uses tools and concepts from density functional theory. We test the method on the driven Hubbard dimer at half filling, and compare exact and approximate results. We show that the proposed method reproduces the average quantum work to high accuracy: for a very large region of parameter space (which cuts across all dynamical regimes) estimates are within 10% of the exact results.
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spelling pubmed-54985382017-07-10 DFT-inspired methods for quantum thermodynamics Herrera, Marcela Serra, Roberto M. D’Amico, Irene Sci Rep Article In the framework of quantum thermodynamics, we propose a method to quantitatively describe thermodynamic quantities for out-of-equilibrium interacting many-body systems. The method is articulated in various approximation protocols which allow to achieve increasing levels of accuracy, it is relatively simple to implement even for medium and large number of interactive particles, and uses tools and concepts from density functional theory. We test the method on the driven Hubbard dimer at half filling, and compare exact and approximate results. We show that the proposed method reproduces the average quantum work to high accuracy: for a very large region of parameter space (which cuts across all dynamical regimes) estimates are within 10% of the exact results. Nature Publishing Group UK 2017-07-05 /pmc/articles/PMC5498538/ /pubmed/28680064 http://dx.doi.org/10.1038/s41598-017-04478-y Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Herrera, Marcela
Serra, Roberto M.
D’Amico, Irene
DFT-inspired methods for quantum thermodynamics
title DFT-inspired methods for quantum thermodynamics
title_full DFT-inspired methods for quantum thermodynamics
title_fullStr DFT-inspired methods for quantum thermodynamics
title_full_unstemmed DFT-inspired methods for quantum thermodynamics
title_short DFT-inspired methods for quantum thermodynamics
title_sort dft-inspired methods for quantum thermodynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498538/
https://www.ncbi.nlm.nih.gov/pubmed/28680064
http://dx.doi.org/10.1038/s41598-017-04478-y
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