Heavy Thermal Dark Matter from a New Collision Mechanism
Bibliographic record
Abstract
We propose a new thermal freeze-out mechanism that results in dark matter masses exceeding the unitarity bound by many orders of magnitude, without violating perturbative unitarity or modifying the standard cosmology. The process determining the relic abundance is $\ensuremath{\chi}{\ensuremath{\zeta}}^{\ifmmode\dagger\else\textdagger\fi{}}\ensuremath{\rightarrow}\ensuremath{\zeta}\ensuremath{\zeta}$, where $\ensuremath{\chi}$ is the dark matter candidate. For ${m}_{\ensuremath{\zeta}}<{m}_{\ensuremath{\chi}}<3{m}_{\ensuremath{\zeta}}$, $\ensuremath{\chi}$ is cosmologically long-lived and scatters against the exponentially more abundant $\ensuremath{\zeta}$. Therefore, such a process allows for exponentially heavier dark matter for the same interaction strength as a particle undergoing ordinary $2\ensuremath{\rightarrow}2$ freeze-out, or equivalently, exponentially weaker interactions for the same mass. We demonstrate this mechanism in a leptophilic dark matter model, which allows for dark matter masses up to ${10}^{9}\text{ }\text{ }\mathrm{GeV}$.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".