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Record W4417246775 · doi:10.48550/arxiv.2504.06698

Emergent metric from wavelet-transformed quantum field theory

2025· preprint· en· W4417246775 on OpenAlexfundno aff
Šimon Vedl, Daniel J. George, Fil Simovic, Dominic G. Lewis, Nicholas Funai, Achim Kempf, Nicolas C. Menicucci, Gavin K. Brennen

Bibliographic record

VenueArXiv.org · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsnot available
FundersCentre of Excellence for Quantum Computation and Communication Technology, Australian Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsMetric (unit)Conformal field theoryQuantum field theoryBoundary (topology)Field (mathematics)Scalar fieldBoundary value problemScalar (mathematics)Conformal map

Abstract

fetched live from OpenAlex

We introduce a method of reverse holography by which a bulk metric is shown to arise from locally computable multiscale correlations of a boundary quantum field theory (QFT). The metric is obtained from the Petz-Rényi mutual information defined with input correlations computed from the continuous wavelet transform. The method is applicable to a variety of boundary QFTs that need not be conformal field theories (CFTs). For thermal free scalar and Dirac field theories the resulting bulk metric is that of (asymmetrically) warped anti-de Sitter (AdS) space. For massless, ground state CFTs the geometry simply reduces to AdS space. We show that certain parameters of the geometry can be tuned by changing the shape of the wavelet function.

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)0.002
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.003
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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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