Mean-field entanglement transitions in random tree tensor networks
Abstract
Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a mean-field theory of such transitions by studying the entanglement properties of random tree tensor networks. As a function of bond dimension, we find a phase transition separating area-law from logarithmic scaling of the entanglement entropy. Using a mapping onto a replica statistical mechanics model defined on a Cayley tree and the cavity method, we analyze the scaling properties of such transitions. Our approach provides a tractable, mean-field-like example of an entanglement transition. Furthermore, we verify our predictions numerically by computing directly the entanglement of random tree tensor network states.
- Authors:
-
- Univ. of Massachusetts, Amherst, MA (United States)
- Publication Date:
- Research Org.:
- Univ. of Massachusetts, Amherst, MA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES)
- OSTI Identifier:
- 1647652
- Grant/Contract Number:
- SC0019168
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Physical Review. B
- Additional Journal Information:
- Journal Volume: 102; Journal Issue: 6; Journal ID: ISSN 2469-9950
- Publisher:
- American Physical Society (APS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; Critical phenomena; Entanglement entropy; Quantum entanglement; Cavity methods; Replica methods; Tensor network methods
Citation Formats
Lopez-Piqueres, Javier, Ware, Brayden, and Vasseur, Romain. Mean-field entanglement transitions in random tree tensor networks. United States: N. p., 2020.
Web. doi:10.1103/physrevb.102.064202.
Lopez-Piqueres, Javier, Ware, Brayden, & Vasseur, Romain. Mean-field entanglement transitions in random tree tensor networks. United States. https://doi.org/10.1103/physrevb.102.064202
Lopez-Piqueres, Javier, Ware, Brayden, and Vasseur, Romain. Thu .
"Mean-field entanglement transitions in random tree tensor networks". United States. https://doi.org/10.1103/physrevb.102.064202. https://www.osti.gov/servlets/purl/1647652.
@article{osti_1647652,
title = {Mean-field entanglement transitions in random tree tensor networks},
author = {Lopez-Piqueres, Javier and Ware, Brayden and Vasseur, Romain},
abstractNote = {Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a mean-field theory of such transitions by studying the entanglement properties of random tree tensor networks. As a function of bond dimension, we find a phase transition separating area-law from logarithmic scaling of the entanglement entropy. Using a mapping onto a replica statistical mechanics model defined on a Cayley tree and the cavity method, we analyze the scaling properties of such transitions. Our approach provides a tractable, mean-field-like example of an entanglement transition. Furthermore, we verify our predictions numerically by computing directly the entanglement of random tree tensor network states.},
doi = {10.1103/physrevb.102.064202},
journal = {Physical Review. B},
number = 6,
volume = 102,
place = {United States},
year = {Thu Aug 06 00:00:00 EDT 2020},
month = {Thu Aug 06 00:00:00 EDT 2020}
}
Web of Science
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