Bibliographic record
Abstract
We investigate the scale-dependence, or the runnings, of linear and second order den-sity perturbations generated in various curvaton scenarios. We argue that the second order perturbations, i.e. non-Gaussianity, can strongly depend on the scale, even when the linear perturbations are nearly scale-invariant. We present analytic formulae for the runnings from curvatons with general energy potentials, and clarify the conditions under which fNL becomes strongly scale-dependent. From the point of view of the fNL running, curvaton potentials can be classified into roughly two categories by whether the potential flattens or steepens com-pared to a quadratic one. As such examples, we study pseudo-Nambu-Goldstone curvatons, and self-interacting curvatons, respectively. The dynamics of non-quadratic curvatons and the behaviors of the resulting density perturbations are clarified by analytical methods. Then we also study models where multiple source can be responsible for density perturbations such as the multi-curvaton, and mixed curvaton and inflaton models where the running of fNL can also be large due to their multi-source nature. We make quantitative analysis for each curvaton scenario and discuss in what cases the scale-dependence, in particular, of fNL can be large enough to be probed with future CMB experiments. ar X iv
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".