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Record W3199559186 · doi:10.1103/physrevd.105.043510

Bubble clustering in cosmological first order phase transitions

2022· article· en· W3199559186 on OpenAlexafffund
Dalila Pîrvu, Jonathan Braden, Matthew C. Johnson

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsCanadian Institute for Theoretical AstrophysicsYork UniversityUniversity of TorontoPerimeter InstituteUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceGovernment of CanadaInnovation, Science and Economic Development CanadaInstitut Périmètre de physique théoriqueSimons Foundation
KeywordsPhysicsFalse vacuumNucleationPhase transitionBubbleStatistical physicsSpacetimeCosmologyInflation (cosmology)UniverseClassical mechanicsTheoretical physicsQuantum mechanicsMechanicsThermodynamics

Abstract

fetched live from OpenAlex

False vacuum decay in quantum mechanical first order phase transitions is a phenomenon with wide implications in cosmology and presents interesting theoretical challenges. In the standard approach, it is assumed that false vacuum decay proceeds through the formation of bubbles that nucleate at random positions in spacetime and subsequently expand. In this paper, we investigate the presence of correlations between bubble nucleation sites using a recently proposed semiclassical stochastic description of vacuum decay. This procedure samples vacuum fluctuations, which are then evolved using classical lattice simulations. We compute the two-point function for bubble nucleation sites from an ensemble of simulations, demonstrating that nucleation sites cluster in a way that is qualitatively similar to peaks in random Gaussian fields. We qualitatively assess the phenomenological implications of bubble clustering in early Universe phase transitions, which include features in the power spectrum of stochastic gravitational waves and an enhancement or suppression of the probability of observing bubble collisions in the eternal inflation scenario.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.417
Teacher spread0.399 · 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 designSimulation or modeling
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

Citations16
Published2022
Admission routes2
Has abstractyes

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