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Record W2041641493 · doi:10.1103/physrevb.91.125119

Edge-entanglement spectrum correspondence in a nonchiral topological phase and Kramers-Wannier duality

2015· article· en· W2041641493 on OpenAlexafffund
Wen Wei Ho, Łukasz Cincio, Heidar Moradi, Davide Gaiotto, Guifré Vidal

Bibliographic record

VenuePhysical Review B · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum many-body systems
Canadian institutionsPerimeter Institute
FundersOntario Ministry of Research, Innovation and ScienceCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaGovernment of CanadaCentre of Excellence for Environmental Decisions, Australian Research CouncilJohn Templeton FoundationOntario Ministry of Economic Development and InnovationSimons Foundation
KeywordsPhysicsQuantum entanglementDegenerate energy levelsHamiltonian (control theory)Topology (electrical circuits)Topological orderDuality (order theory)Symmetry protected topological orderSpectral lineQuantum mechanicsQuantumMathematicsCombinatorics

Abstract

fetched live from OpenAlex

For chiral topological phases there exist analytical proofs of a one-to-one correspondence between the low lying spectrum of edge states and that of the entanglement spectrum. Whether or not such an edge-entanglement spectrum correspondence could apply to non-chiral phases has been unclear. Here it is shown that in the Wen-plaquette model, a non-chiral ${Z}_{2}$ topological phase, such a correspondence is exact in the absence of perturbations. While no such correspondence exists in the case of a general perturbation, the correspondence can be shown to apply for perturbations restricted to be translation invariant along the edge/entanglement cut.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.393
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations47
Published2015
Admission routes2
Has abstractyes

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