Bibliographic record
Abstract
Dark matter (DM) could be a nonthermal relic that freezes in from extremely weak, sub-Hubble annihilation and decay of Standard Model (SM) particles. The case of Dirac DM freezing in via a dark photon mediator is a well-studied benchmark for DM direct detection experiments. Here, we extend prior work to take into account the possibility that DM is pseudo-Dirac with a small mass splitting. If the mass splitting is greater than twice the electron mass but less than the dark photon mass, there will be distinct cosmological signatures. The excited state ${\ensuremath{\chi}}_{2}$ is initially produced in equal abundance to the ground state ${\ensuremath{\chi}}_{1}$. Due to the small couplings needed to explain the observed relic abundance, the excited state population can decay at late cosmological times, primarily via the three-body process ${\ensuremath{\chi}}_{2}\ensuremath{\rightarrow}{\ensuremath{\chi}}_{1}{e}^{+}{e}^{\ensuremath{-}}$. This injects energetic electrons into the ambient environment, providing observable signatures involving big bang nucleosynthesis, cosmic microwave background spectral distortions and anisotropies, and the Lyman-$\ensuremath{\alpha}$ forest. Furthermore, the ground state particles that are populated from the three-body decay receive a velocity kick, with implications for DM clustering on small scales. Inelastic freeze-in thus gives a motivated decaying DM candidate, where the long lifetimes are connected to the relic abundance mechanism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.006 |
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".