Time-dependent variational principle for open quantum systems with artificial neural networks

• Verfasst von: Reh, Moritz [VerfasserIn]
• Verfasst von: Schmitt, Markus [VerfasserIn]
• Verfasst von: Gärttner, Martin [VerfasserIn]
• Titel: Time-dependent variational principle for open quantum systems with artificial neural networks
• Verf.angabe: Moritz Reh, Markus Schmitt, and Martin Gärttner
• E-Jahr: 2021
• Jahr: 1 December 2021
• Umfang: 7 S.
• Fussnoten: Gesehen am 17.12.2021
• Titel Quelle: Enthalten in: Physical review letters
• Ort Quelle: College Park, Md. : APS, 1958
• Jahr Quelle: 2021
• Band/Heft Quelle: 127(2021), 23, Artikel-ID 230501, Seite 1-7
• ISSN Quelle: 1079-7114
• DOI: doi:10.1103/PhysRevLett.127.230501
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1782431217

Abstract

We develop a variational approach to simulating the dynamics of open quantum many-body systems using deep autoregressive neural networks. The parameters of a compressed representation of a mixed quantum state are adapted dynamically according to the Lindblad master equation by employing a time-dependent variational principle. We illustrate our approach by solving the dissipative quantum Heisenberg model in one dimension for up to 40 spins and in two dimensions for a 4×4 system and by applying it to the simulation of confinement dynamics in the presence of dissipation.