Eigenstate thermalization hypothesis and approximate quantum error correction
Abstract
The eigenstate thermalization hypothesis (ETH) is a powerful conjecture for understanding how statistical mechanics emerges in a large class of many-body quantum systems. It has also been interpreted in a CFT context, and, in particular, holographic CFTs are expected to satisfy ETH. Recently, it was observed that the ETH condition corresponds to a necessary and sufficient condition for an approximate quantum error correcting code (AQECC), implying the presence of AQECCs in systems satisfying ETH. In this paper, we explore the properties of ETH as an error correcting code and show that there exists an explicit universal recovery channel for the code. Based on the analysis, we discuss a generalization that all chaotic theories contain error correcting codes. We then specialize to AdS/CFT to demonstrate the possibility of total bulk reconstruction in black holes with a well-defined macroscopic geometry. When combined with the existing AdS/CFT error correction story, this shows that black holes are enormously robust against erasure errors.
- Authors:
-
- Berkeley Center for Theoretical Physics, Berkeley, CA (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
- Berkeley Center for Theoretical Physics, Berkeley, CA (United States)
- Publication Date:
- Research Org.:
- Brookhaven National Lab. (BNL), Upton, NY (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21)
- OSTI Identifier:
- 1566871
- Report Number(s):
- BNL-212136-2019-JAAM
Journal ID: ISSN 1029-8479; TRN: US2001008
- Grant/Contract Number:
- SC0012704
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of High Energy Physics (Online)
- Additional Journal Information:
- Journal Name: Journal of High Energy Physics (Online); Journal Volume: 2019; Journal Issue: 8; Journal ID: ISSN 1029-8479
- Publisher:
- Springer Berlin
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; AdS-CFT Correspondence; Black Holes in String Theory; Conformal Field Theory
Citation Formats
Bao, Ning, and Cheng, Newton. Eigenstate thermalization hypothesis and approximate quantum error correction. United States: N. p., 2019.
Web. doi:10.1007/JHEP08(2019)152.
Bao, Ning, & Cheng, Newton. Eigenstate thermalization hypothesis and approximate quantum error correction. United States. https://doi.org/10.1007/JHEP08(2019)152
Bao, Ning, and Cheng, Newton. Tue .
"Eigenstate thermalization hypothesis and approximate quantum error correction". United States. https://doi.org/10.1007/JHEP08(2019)152. https://www.osti.gov/servlets/purl/1566871.
@article{osti_1566871,
title = {Eigenstate thermalization hypothesis and approximate quantum error correction},
author = {Bao, Ning and Cheng, Newton},
abstractNote = {The eigenstate thermalization hypothesis (ETH) is a powerful conjecture for understanding how statistical mechanics emerges in a large class of many-body quantum systems. It has also been interpreted in a CFT context, and, in particular, holographic CFTs are expected to satisfy ETH. Recently, it was observed that the ETH condition corresponds to a necessary and sufficient condition for an approximate quantum error correcting code (AQECC), implying the presence of AQECCs in systems satisfying ETH. In this paper, we explore the properties of ETH as an error correcting code and show that there exists an explicit universal recovery channel for the code. Based on the analysis, we discuss a generalization that all chaotic theories contain error correcting codes. We then specialize to AdS/CFT to demonstrate the possibility of total bulk reconstruction in black holes with a well-defined macroscopic geometry. When combined with the existing AdS/CFT error correction story, this shows that black holes are enormously robust against erasure errors.},
doi = {10.1007/JHEP08(2019)152},
journal = {Journal of High Energy Physics (Online)},
number = 8,
volume = 2019,
place = {United States},
year = {2019},
month = {8}
}
Web of Science
Figures / Tables:

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