Resonant pseudo-Dirac dark matter as a sub-GeV thermal target
Bibliographic record
Abstract
Dark matter (DM) could be a pseudo-Dirac thermal relic with a small mass splitting that is coupled off diagonally to a kinetically mixed dark photon. This model, particularly in the sub-GeV mass range, is a key benchmark for accelerator searches and direct detection experiments. Typically, the presence of even a tiny fraction of pseudo-Dirac DM in the excited state around the time of recombination would be excluded by DM annihilation bounds from the cosmic microwave background (CMB); thus, viable thermal histories must typically feature an exponential suppression of the excited state. We revisit assumptions about the thermal history in the resonant regime, where the dark photon mass is slightly more than twice the DM mass (to within ∼10% ), leading to an s -channel resonance in the annihilation cross section. This resonance substantially reduces the couplings required for achieving the observed relic abundance, implying that in much of the parameter space, the DM kinetically decouples from the Standard Model well before the final DM relic abundance is achieved. We find that the excited state is not thermally depopulated in this regime. In spite of this, we find that the presence of the excited state does violate CMB bounds, even for arbitrarily small mass splittings. The present-day abundance of the excited state opens up the possibility of signatures that are usually not relevant for pseudo-Dirac DM, including indirect detection, direct detection, and self-interacting DM signatures. Published by the American Physical Society 2024
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".