Signatures of large composite Dark Matter states
Bibliographic record
Abstract
We investigate the interactions of large composite dark matter (DM) states with the Standard Model (SM) sector. Elastic scattering with SM nuclei can be coherently enhanced by factors as large as A2, where A is the number of constituents in the composite state (there exist models in which DM states of very large A ≳ 108 may be realised). This enhancement, for a given direct detection event rate, weakens the expected signals at colliders by up to 1/A. Moreover, the spatially extended nature of the DM states leads to an additional, characteristic, form factor modifying the momentum dependence of scattering processes, altering the recoil energy spectra in direct detection experiments. In particular, energy recoil spectra with peaks and troughs are possible, and such features could be confirmed with only $$ \mathcal{O}(50) $$ events, independently of the assumed halo velocity distribution. Large composite states also generically give rise to low-energy collective excitations potentially relevant to direct detection and indirect detection phenomenology. We compute the form factor for a generic class of such excitations — quantised surface modes — finding that they can lead to coherently-enhanced, but generally sub-dominant, inelastic scattering in direct detection experiments. Finally, we study the modifications to capture rates in astrophysical objects that follow from the elastic form factor, as well as the effects of inelastic interactions between DM states once captured. We argue that inelastic interactions may lead to the DM collapsing to a dense configuration at the centre of the object.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".