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Record W4400141908 · doi:10.48550/arxiv.2406.19169

Spikes and spines in 3D Lorentzian simplicial quantum gravity

2024· preprint· en· W4400141908 on OpenAlexfundno aff
Johanna N. Borissova, Bianca Dittrich, Dongxue Qu, Marc Schiffer

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicNoncommutative and Quantum Gravity Theories
Canadian institutionsnot available
FundersInstitut Périmètre de physique théoriqueNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaMinistry of Colleges and UniversitiesInnovation, Science and Economic Development Canada
KeywordsQuantumQuantum gravityTheoretical physicsPhysicsPure mathematicsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

Simplicial approaches to quantum gravity such as Quantum Regge Calculus and Spin Foams include configurations where bulk edges can become arbitrarily large while keeping the lengths of the boundary edges small. Such configurations pose significant challenges in Euclidean Quantum Regge Calculus, as they lead to infinities for the partition function and length expectation values. Here we investigate such configurations in three-dimensional Lorentzian Quantum Regge Calculus, and find that the partition function and length expectation values remain finite. This shows that the Lorentzian approach can avoid a key issue of the Euclidean approach. We also find that the space of configurations, for which bulk edges can become very large, is much richer than in the Euclidean case. In particular, it includes configurations with irregular light-cone structures, which lead to imaginary terms in the Regge action and branch cuts along the Lorentzian path integral contour. Hence, to meaningfully define the Lorentzian Regge path integral, one needs to clarify how such configurations should be handled.

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)0.000
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.002
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 head0.043
GPT teacher head0.216
Teacher spread0.173 · 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
Published2024
Admission routes1
Has abstractyes

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