Bibliographic record
Abstract
A bstract Supercooled phase transitions, as predicted, e.g., in near-conformal and confining extensions of the Standard Model (SM), are established sources of strong stochastic gravitational wave backgrounds (SGWBs). In this work, we investigate another facet of such transitions: their significant and largely uncharted impact on gravitational wave spectra originating from independent cosmological sources. Focusing on gravitational waves produced by a metastable cosmic string network, we show that an intervening supercooled phase, initiating thermal inflation, can reshape and suppress the high-frequency part of the spectrum. This mechanism reopens regions of string parameter space previously excluded by LIGO’s null results, while remaining compatible with the nanohertz SGWB signal reported by pulsar timing arrays (PTAs). The resulting total spectrum typically exhibits a dual-component structure, sourced by both string decay and the phase transition itself, rendering the scenario observationally distinctive. We systematically classify the viable parameter space and identify regions accessible to upcoming detectors such as Advanced LIGO, LISA, and ET.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".