Constraints on γ-CDM interactions matching the Planck data precision
Bibliographic record
Abstract
The Planck experiment has measured the Cosmic Microwave Background (CMB) angular spectrum with unprecedented accuracy, and these results are likely to remain the state-of-the art for a decade or more. Since these measurements are going to be used to forecast Euclid's ability to test alternative dark matter models, we aim to set the final CMB constraint on the cross section of dark matter-photon scattering in the early universe. As the formalism has not been published in the literature yet, we present the key steps to derive the full set of linearized Einstein and Boltzmann equations and elucidate necessary modifications to the line of sight and the tight coupling approximation. These approximation schemes are commonly used in Boltzmann codes to reduce computational costs, but the tight coupling regime has been neglected in previous works related to dark matter-photon interactions. Our computations account for a dark matter sound speed, which was neglected in previous work. We find that its effect is negligible on the CMB spectra but fairly important on the linear matter power spectrum. We then analyse the Planck data, with and without the 2015 polarisation data at high multipoles. In both cases our constraint on the ratio of the elastic scattering cross section to the dark matter mass becomes more stringent with respect to previous constraints. The change is about 35% when the full Planck dataset is added (which includes E-mode polarisation at high multipoles and the lensing potential power spectrum) and about 20%. when we only account for the polarisation data at low multipoles and the full temperature spectrum. Our most conservative limit reads as σ DM −γ ⩽ 2.25 × 10 −6 σ Th ( m DM /GeV) at 95% confidence. We do not expect this limit to change by adding the recently published SPT data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".