Observation of nonlinear response and Onsager regression in a photon Bose-Einstein condensate.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
03 Jun 2024
03 Jun 2024
Historique:
received:
27
02
2024
accepted:
22
05
2024
medline:
4
6
2024
pubmed:
4
6
2024
entrez:
3
6
2024
Statut:
epublish
Résumé
The quantum regression theorem states that the correlations of a system at two different times are governed by the same equations of motion as the single-time averages. This provides a powerful framework for the investigation of the intrinsic microscopic behaviour of physical systems by studying their macroscopic response to a controlled external perturbation. Here we experimentally demonstrate that the two-time particle number correlations in a photon Bose-Einstein condensate inside a dye-filled microcavity exhibit the same dynamics as the response of the condensate to a sudden perturbation of the dye molecule bath. This confirms the regression theorem for a quantum gas, and, moreover, demonstrates it in an unconventional form where the perturbation acts on the bath and only the condensate response is monitored. For strong perturbations, we observe nonlinear relaxation dynamics which our microscopic theory relates to the equilibrium fluctuations, thereby extending the regression theorem beyond the regime of linear response.
Identifiants
pubmed: 38830905
doi: 10.1038/s41467-024-49064-9
pii: 10.1038/s41467-024-49064-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4730Subventions
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 101040409
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 277625399
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : EXC 2004/1-390534769
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 847471
Informations de copyright
© 2024. The Author(s).
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