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  Optimal Sampling of Dynamical Large Deviations in Two Dimensions via Tensor Networks

Causer, L., Bañuls, M. C., & Garrahan, J. P. (2023). Optimal Sampling of Dynamical Large Deviations in Two Dimensions via Tensor Networks. Physical Review Letters, 130(14): 147401. doi:10.1103/PhysRevLett.130.147401.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-7800-C Version Permalink: https://hdl.handle.net/21.11116/0000-000D-7803-9
Genre: Journal Article

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 Creators:
Causer, Luke1, Author
Bañuls, Mari Carmen2, 3, Author           
Garrahan, Juan P.1, Author
Affiliations:
1external, ou_persistent22              
2Theory, Max Planck Institute of Quantum Optics, Max Planck Society, ou_1445571              
3MCQST - Munich Center for Quantum Science and Technology, External Organizations, ou_3330166              

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Language(s): eng - English
 Dates: 2022-10-172023-03-202023-04-042023-04-07
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1103/PhysRevLett.130.147401
arXiv: 2209.11788
Other: 6442
 Degree: -

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Funding program : Germany’s Excellence Strategy—EXC-2111–390814868
Funding organization : Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)

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Title: Physical Review Letters
  Abbreviation : Phys. Rev. Lett.
Source Genre: Journal
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Publ. Info: Woodbury, N.Y. : American Physical Society
Pages: - Volume / Issue: 130 (14) Sequence Number: 147401 Start / End Page: - Identifier: ISSN: 0031-9007
CoNE: https://pure.mpg.de/cone/journals/resource/954925433406_1