Implications of the observation of dark matter self-interactions for singlet scalar dark matter
Bibliographic record
Abstract
Evidence for dark matter self-interactions has recently been reported based on the observation of a spatial offset between the dark matter halo and the stars in a galaxy in the cluster Abell 3827. Interpreting the offset as due to dark matter self-interactions leads to a cross section measurement of ${\ensuremath{\sigma}}_{\mathrm{DM}}/m\ensuremath{\sim}(1--1.5)\text{ }\text{ }{\mathrm{cm}}^{2}\text{ }{\mathrm{g}}^{\ensuremath{-}1}$, where $m$ is the mass of the dark matter particle. We use this observation to constrain singlet scalar dark matter coupled to the standard model and to two-Higgs-doublet models. We show that the most natural scenario in this class of models is very light dark matter, below about 0.1 GeV, whose relic abundance is set by freeze-in, i.e., by slow production of dark matter in the early universe via extremely tiny interactions with the Higgs boson, never reaching thermal equilibrium. We also show that the dark matter abundance can be established through the usual thermal freeze-out mechanism in the singlet scalar extension of the Yukawa-aligned two-Higgs-doublet model, but that it requires rather severe fine tuning of the singlet scalar mass.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".