Petz reconstruction in random tensor networks

Hewei Frederic Jia; Mukund Rangamani

Petz reconstruction in random tensor networks

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2006.12601 v2 pith:TXOJ72U6 submitted 2020-06-22 hep-th quant-ph

Hewei Frederic Jia , Mukund Rangamani This is my paper · ORCID

classification hep-thquant-ph

keywords randomreconstructionbulkpetztensorboundarycoarse-grainingcomment

verification ladder T0 review T1 audit T2 compute T3 formal

0 comments

read the original abstract

We illustrate the ideas of bulk reconstruction in the context of random tensor network toy models of holography. Specifically, we demonstrate how the Petz reconstruction map works to obtain bulk operators from the boundary data by exploiting the replica trick. We also take the opportunity to comment on the differences between coarse-graining and random projections.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Hollow-grams: Generalized Entanglement Wedges from the Gravitational Path Integral
hep-th 2025-06 conditional novelty 7.0 of 10

The entropy of a bulk region in holographic states equals the generalized entropy of the smallest wedge containing it, derived from a replica path integral via a hollow-graphic construction.

Pith tools