TESTING FOR FEATURES IN THE PRIMORDIAL POWER SPECTRUM
Bibliographic record
Abstract
Well-known causality arguments show that events occurring during or at the end of inflation, associated with reheating or preheating, could contribute a blue component to the spectrum of primordial curvature perturbations, with the dependence k3. We explore the possibility that they could be observably large in CMB, LSS, and Lyman-α data. We find that a k3 component with a cutoff at some maximum k can modestly improve the fits (Δχ2 = 2.0, 5.4) of the low multipoles (ℓ ~ 10–50) or the second peak (ℓ ~ 540) of the CMB angular spectrum when the three-year WMAP data are used. Moreover, the results from WMAP are consistent with the CBI, ACBAR, 2dFGRS, and SDSS data when they are included in the analysis. Including the SDSS galaxy clustering power spectrum, we find weak positive evidence for the k3 component at the level of Δχ2′ = 2.4, with the caveat that the nonlinear evolution of the power spectrum may not be properly treated in the presence of the k3 distortion. To investigate the high-k regime, we use the Lyman-α forest data (LUQAS, Croft et al., and SDSS Lyman-α); here we find evidence at the level Δχ2′ = 3.8. Considering that there are two additional free parameters in the model, the above results do not give a strong evidence for features; however, they show that surprisingly large bumps are not ruled out. We give constraints on the ratio between the k3 component and the nearly scale-invariant component, r3 < 1.5, over the range of wave numbers 2.3 × 10-3 Mpc -1 < k < 8.2 Mpc -1. We also discuss theoretical models which could lead to the k3 effect, including ordinary hybrid inflation and double D-term inflation models. We show that the well-motivated k3 component is also a good representative of the generic spikelike feature in the primordial perturbation power spectrum.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".