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Record W4400572730 · doi:10.48550/arxiv.2407.06263

Thermal False Vacuum Decay Is More Than It Seems

2024· preprint· en· W4400572730 on OpenAlexfundno aff
Dalila Pîrvu, Andrey Shkerin, Sergey Sibiryakov

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
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
KeywordsFalse vacuumPhysicsThermalTheoretical physicsThermodynamics

Abstract

fetched live from OpenAlex

We study the decay of a thermally excited metastable vacuum in classical field theory using real-time numerical simulations. We find a significantly lower decay rate than predicted by standard thermal theory at moderate temperatures, $E_b/T\sim 10$, where $E_b$ is the critical bubble energy. The discrepancy is due to the violation of thermal equilibrium during the critical bubble nucleation and is reduced if thermalization is enhanced by introduction of dissipation and thermal noise. We formulate a condition for the system to remain in equilibrium during the nucleation process and show that it is generally violated in weakly coupled field theories. Nevertheless, we argue that the violation of thermal equilibrium becomes irrelevant for the false vacuum decay rate at sufficiently low temperatures and the standard thermal rate is recovered.

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)0.006
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.073
GPT teacher head0.223
Teacher spread0.150 · 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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