Cosmology and signals of light pseudo-Dirac dark matter
Bibliographic record
Abstract
Abstract In this paper, we analyze the cosmological evolution, allowed parameter space, and observational prospects for a dark sector consisting of thermally produced pseudo-Dirac fermions with a small mass splitting, coupled to the Standard Model through a dark photon. This scenario is particularly notable in the context of sub-GeV dark matter, where the mass-off-diagonal leading interaction limits applicability of both CMB energy injection constraints and standard direct detection searches. We present the first general study of the thermal history of pseudo-Dirac DM with splittings from 100 eV to MeV, focusing on the depletion of the heavier “excited” state abundance via scatterings and decays, and on the distinctive signals arising from its small surviving abundance. We analyze CMB energy injection bounds on both DM annihilation and decay, accelerator-based probes, and new line-like direct-detection signals from the excited DM down-scattering on either nuclei or electrons, as well as future search prospects in each channel. We also comment on the relevance of this signal to the few-keV Xenon1T electron excess and on possible diurnal modulation of this signal, and introduce a signal-strength parametrization to facilitate the comparison of future experimental results to theoretical expectations.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".