Ultra-light axions and the S <sub>8</sub> tension: joint constraints from the cosmic microwave background and galaxy clustering
Bibliographic record
Abstract
Abstract We search for ultra-light axions as dark matter (DM) and dark energy particle candidates, for axion masses 10 -32 eV ≤ m a ≤ 10 -24 eV, by a joint analysis of cosmic microwave background (CMB) and galaxy clustering data — and consider if axions can resolve the tension in inferred values of the matter clustering parameter S 8 . We give legacy constraints from Planck 2018 CMB data, improving 2015 limits on the axion density Ω a h 2 by up to a factor of three; CMB data from the Atacama Cosmology Telescope and the South Pole Telescope marginally weaken Planck bounds at m a = 10 -25 eV, owing to lower (and theoretically-consistent) gravitational lensing signals. We jointly infer, from Planck CMB and full-shape galaxy power spectrum and bispectrum data from the Baryon Oscillation Spectroscopic Survey (BOSS), that axions are, today, < 10% of the DM for m a ≤ 10 -26 eV and < 1% for 10 -30 eV ≤ m a ≤ 10 -28 eV. BOSS data strengthen limits, in particular at higher m a by probing high-wavenumber modes ( k < 0.4 h Mpc -1 ). BOSS alone finds a preference for axions at 2.7 σ , for m a = 10 -26 eV, but Planck disfavours this result. Nonetheless, axions in a window 10 -28 eV ≤ m a ≤ 10 -25 eV can improve consistency between CMB and galaxy clustering data, e.g., reducing the S 8 discrepancy from 2.7 σ to 1.6 σ , since these axions suppress structure growth at the 8 h -1 Mpc scales to which S 8 is sensitive. We expect improved constraints with upcoming high-resolution CMB and galaxy lensing and future galaxy clustering data, where we will further assess if axions can restore cosmic concordance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".