Record link: 
http://hdl.handle.net/20.500.12708/202603
-
Title: 
Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium
en
Citation: 
Carnazza, F., Carollo, F., Andergassen, S., Martius, G., Klopotek, M., & Lesanovsky, I. (2024). Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium. MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 5(4), Article 045002. https://doi.org/10.1088/2632-2153/ad7ad7
-
Publisher DOI: 
10.1088/2632-2153/ad7ad7
-
Publication Type: 
Article - Original Research Article
en
Language: 
English
-
Authors: 
Carnazza, Francesco 
Carollo, Federico 
Andergassen, Sabine 
Martius, Georg 
Klopotek, Miriam 
Lesanovsky, Igor 
-
Organisational Unit: 
E194-06 - Forschungsbereich Machine Learning 
-
Journal: 
MACHINE LEARNING-SCIENCE AND TECHNOLOGY 
-
ISSN: 
2632-2153
-
Date (published): 
7-Oct-2024
-
Number of Pages: 
16
-
Publisher: 
IOP PUBLISHING LTD
-
Peer reviewed: 
Yes
-
Keywords: 
Machine learning; stochastic differential equations
en
Research Areas: 
Quantum Many-body Systems Physics: 50%
Information Systems Engineering: 50%
-
Science Branch: 
1020 - Informatik: 50%
1030 - Physik, Astronomie: 50%
-
Appears in Collections:
Article

Show full item record

Page view(s)

60
checked on Oct 22, 2024

Google ScholarTM

Check