New Constraints on the free-streaming of warm dark matter from intermediate and small scale Lyman-$α$ forest data
Bibliographic record
Abstract
We present new measurements of the free-streaming of warm dark matter (WDM) from Lyman-α flux-power spectra. We use data from the medium resolution, intermediate redshift XQ-100 sample observed with the X-shooter spectrograph (z=3–4.2) and the high-resolution, high-redshift sample used in Viel et al. (2013) obtained with the HIRES/MIKE spectrographs (z=4.2–5.4). Based on further improved modelling of the dependence of the Lyman-α flux-power spectrum on the free-streaming of dark matter, cosmological parameters, as well as the thermal history of the intergalactic medium (IGM) with hydrodynamical simulations, we obtain the following limits, expressed as the equivalent mass of thermal relic WDM particles. The XQ-100 flux power spectrum alone gives a lower limit of 1.4 keV, the re-analysis of the HIRES/MIKE sample gives 4.1 keV while the combined analysis gives our best and significantly strengthened lower limit of 5.3 keV (all 2σ C.L.). The further improvement in the joint analysis is partly due to the fact that the two data sets have different degeneracies between astrophysical and cosmological parameters that are broken when the data sets are combined, and more importantly on chosen priors on the thermal evolution. These results all assume that the temperature evolution of the IGM can be modeled as a power law in redshift. Allowing for a nonsmooth evolution of the temperature of the IGM with sudden temperature changes of up to 5000 K reduces the lower limit for the combined analysis to 3.5 keV. A WDM with smaller thermal relic masses would require, however, a sudden temperature jump of 5000 K or more in the narrow redshift interval z=4.6–4.8, in disagreement with observations of the thermal history based on high-resolution resolution Lyman-α forest data and expectations for photo-heating and cooling in the low density IGM at these redshifts.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".