CMB temperature trispectrum from accreting primordial black holes
Bibliographic record
Abstract
It is known that primordial black holes (PBHs) can leave an imprint on cosmic microwave background (CMB) anisotropy power spectra, due to their accretion-powered injection of energy into the recombining plasma. Here we study a qualitatively new CMB observable sourced by accreting PBHs: the temperature trispectrum or connected four-point function. This non-Gaussian signature is due to the strong spatial modulation of the PBH accretion luminosity, thus ionization perturbations, by large-scale supersonic relative velocities between PBHs and the accreted baryons. We first derive a factorizable quadratic transfer function for free-electron fraction inhomogeneities induced by accreting PBHs. We then compute the perturbation to the CMB temperature anisotropy due to a general modification of recombination and apply our results to accreting PBHs. We calculate a new contribution to the temperature power spectrum due to the spatial fluctuations of the ionization perturbation induced by accreting PBHs, going beyond past studies that only accounted for its homogeneous part. While these contributions are formally comparable, we find the new part to be subdominant due to the poor correlation of the perturbed temperature field with the standard CMB anisotropy. For the first time, we compute the temperature trispectrum due to accreting PBHs. This trispectrum is weakly correlated with the local-type primordial non-Gaussianity trispectrum; hence constraints on the latter do not lead to competitive bounds on accreting PBHs. We also forecast Planck's sensitivity to the temperature trispectrum sourced by accreting PBHs. Excitingly, we find it to be more sensitive to PBHs under $\ensuremath{\sim}{10}^{3}{M}_{\ensuremath{\bigodot}}$ than current temperature-only power-spectrum constraints. This result motivates our future work extending this study to temperature and polarization trispectra induced by inhomogeneously accreting PBHs.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".