Record link: 
http://hdl.handle.net/20.500.12708/196492
-
Title: 
Inferring interpretable dynamical generators of local quantum observables from projective measurements through machine learning
en
Citation: 
Cemin, G., Carnazza, F., Andergassen, S., Martius, G., Carollo, F., & Lesanovsky, I. (2024). Inferring interpretable dynamical generators of local quantum observables from projective measurements through machine learning. Physical Review Applied, 21(4), Article L041001. https://doi.org/10.1103/PhysRevApplied.21.L041001
-
Publisher DOI: 
10.1103/PhysRevApplied.21.L041001
-
Publication Type: 
Article - Original Research Article
en
Language: 
English
-
Authors: 
Cemin, Giovanni 
Carnazza, Francesco 
Andergassen, Sabine 
Martius, Georg 
Carollo, Federico 
Lesanovsky, Igor 
-
Organisational Unit: 
E194-06 - Forschungsbereich Machine Learning 
-
Journal: 
Physical Review Applied 
-
ISSN: 
2331-7019
-
Date (published): 
3-Apr-2024
-
Number of Pages: 
6
-
Publisher: 
AMER PHYSICAL SOC
-
Peer reviewed: 
Yes
-
Keywords: 
Artificial neural networks; Open quantum systems; decoherence; Quantum algorithms; Nonequilibrium lattice models; Quantum many-body systems; Quantum spin models; Lindblad equation; Machine learning
en
Research Areas: 
Quantum Many-body Systems Physics: 50%
Modeling and Simulation: 50%
-
Science Branch: 
1020 - Informatik: 40%
1030 - Physik, Astronomie: 60%
-
Appears in Collections:
Article

Show full item record

Page view(s)

104
checked on Apr 9, 2024

Google ScholarTM

Check