Electroweak phase transition in two scalar singlet model with pNGB dark matter
Bibliographic record
Abstract
A bstract We investigate the dynamics of the electroweak phase transition within an extended Standard Model framework that includes one real scalar (Φ) and one complex scalar ( S ), both of which are SM gauge singlets. The global U(1) symmetry is softly broken to a $$ {\mathcal{Z}}_3 $$ Z 3 symmetry by the S 3 term in the scalar potential. After this U(1) symmetry breaking, the imaginary component of the complex scalar ( S ) acts as a pseudo-Nambu-Goldstone boson (pNGB) dark matter candidate, naturally stabilized by the $$ {\mathcal{Z}}_2 $$ Z 2 symmetry of the scenario. Specially, the spontaneous breaking of the global U(1) symmetry to a discrete $$ {\mathcal{Z}}_3 $$ Z 3 subgroup can introduce effective cubic terms in the scalar potential, which facilitates a strong first-order phase transition. We analyze both single-step and multi-step first-order phase transitions, identifying the parameter space that satisfies the dark matter relic density constraints, complies with all relevant experimental constraints, and exhibits a strong first-order electroweak phase transition. The interplay of these criteria significantly restricts the model parameter space, often leading to an underabundant relic density. Moreover, we delve into the gravitational wave signatures associated with this framework, offering valuable insights that complement traditional dark matter direct and indirect detection methods.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".