2025-02-22T17:47:17-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: Query fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22irk-123456789-157119%22&qt=morelikethis&rows=5
2025-02-22T17:47:17-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: => GET http://localhost:8983/solr/biblio/select?fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22irk-123456789-157119%22&qt=morelikethis&rows=5
2025-02-22T17:47:17-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: <= 200 OK
2025-02-22T17:47:17-05:00 DEBUG: Deserialized SOLR response
A machine learning approach to the Berezinskii-Kosterlitz-Thouless transition in classical and quantum models

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 task. In...

Full description

Saved in:
Bibliographic Details
Main Authors: Richter-Laskowska, M., Khan, H., Trivedi, N., Maśka, M.M.
Format: Article
Language:English
Published: Інститут фізики конденсованих систем НАН України 2018
Series:Condensed Matter Physics
Online Access:http://dspace.nbuv.gov.ua/handle/123456789/157119
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://dspace.nbuv.gov.ua/handle/123456789/157119

Similar Items