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A machine learning approach to the Berezinskii-Kosterlitz-Thouless transition in classical and quantum models

The Berezinskii-Kosterlitz-Thouless transition is a very specific phase transition where all thermodynamic quantities are smooth. Therefore, it is difficult to determine the critical temperature in a precise way. In this paper we demonstrate how neural networks can be used to perform this t...

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Bibliographic Details
Published in:	Condensed Matter Physics
Date:	2018
Main Authors:	Richter-Laskowska, M., Khan, H., Trivedi, N., Maśka, M.M.
Format:	Article
Language:	English
Published:	Інститут фізики конденсованих систем НАН України 2018
Online Access:	https://nasplib.isofts.kiev.ua/handle/123456789/157119
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Journal Title:	Digital Library of Periodicals of National Academy of Sciences of Ukraine
Cite this:	A machine learning approach to the Berezinskii-Kosterlitz-Thouless transition in classical and quantum models / M. Richter-Laskowska, H. Khan, N. Trivedi, M.M. Maśka // Condensed Matter Physics. — 2018. — Т. 21, № 3. — С. 33602: 1–11. — Бібліогр.: 32 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine

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