Many-body localization in the age of classical computing *
Institute of Photonic Sciences · Institució Catalana de Recerca i Estudis Avançats · +5 more institutions
Abstract
Abstract Statistical mechanics provides a framework for describing the physics of large, complex many-body systems using only a few macroscopic parameters to determine the state of the system. For isolated quantum many-body systems, such a description is achieved via the eigenstate thermalization hypothesis (ETH), which links thermalization, ergodicity and quantum chaotic behavior. However, tendency towards thermalization is not observed at finite system sizes and evolution times in a robust many-body localization (MBL) regime found numerically and experimentally in the dynamics of interacting many-body systems at strong disorder. Although the phenomenology of the MBL regime is well-established, the central…
Citation impact
- FWCI
- 36.11
- Percentile
- 100%
- References
- 778
Authors
5- PSPiotr SierantCorresponding
Institute of Photonic Sciences
- MLMaciej Lewenstein
Institució Catalana de Recerca i Estudis Avançats, Institute of Photonic Sciences, Centre Tecnologic de Telecomunicacions de Catalunya
- ASAntonello Scardicchio
The Abdus Salam International Centre for Theoretical Physics (ICTP)
- LVLev Vidmar
University of Ljubljana, Jožef Stefan Institute
- JZJakub Zakrzewski
Jagiellonian University
Topics & keywords
- Physics
- Ergodicity
- Statistical physics
- Thermalisation
- Quantum chaos
- Quantum
- Scaling
- Thermodynamic limit
Funding
- ECEuropean CommissionAwards: PRTR-C17.I1, PCI2019-111828-2, 13039/501100011033, 501100011033, C17.I1, PE00000023, PRTR-C17, PCI2022-132919
- JAJavna Agencija za Raziskovalno Dejavnost RSAwards: P1-0044, P1-0044, N1-0273, J1-50005, and N1-0369
- NCNarodowym Centrum NaukiAward: OPUS grant No. OPUS18 2019/35/B/ST2/00034 and the
- IPInfrastruktura PL-Grid
- QQuantERAAwards: DYNAMITE PCI2022-132919, PCI2019-111828-2, PCI2022-132919, MAQS PCI2019-111828-2
- EREuropean Research Council
- AEAgencia Estatal de InvestigaciónAwards: PRTR-C17.I1, 501100011033, CEX2019-000910-S, 13039, PCI2019-111828-2, PID2022-139099NB, 0011033, PCI2022-132919, AEI/10, 13039/501100011033, PID2022-139099NB-I00, CEX2019-000910, PID2019-106901GB-I00, PID2019
- ACAcademic Computer Centre Cyfronet, AGH University of Science and Technology