(In)direct detection of boosted dark matter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We initiate the study of novel thermal dark matter (DM) scenarios where present-day annihilation of DM in the galactic center produces boosted stable particles in the dark sector. These stable particles are typically a subdominant DM component, but because they are produced with a large Lorentz boost in this process, they can be detected in large volume terrestrial experiments via neutral-current-like interactions with electrons or nuclei. This novel DM signal thus combines the production mechanism associated with indirect detection experiments (i.e. galactic DM annihilation) with the detection mechanism associated with direct detection experiments (i.e. DM scattering off terrestrial targets). Such processes are generically present in multi-component DM scenarios or those with non-minimal DM stabilization symmetries. As a proof of concept, we present a model of two-component thermal relic DM, where the dominant heavy DM species has no tree-level interactions with the standard model and thus largely evades direct and indirect DM bounds. Instead, its thermal relic abundance is set by annihilation into a subdominant lighter DM species, and the latter can be detected in the boosted channel via the same annihilation process occurring today. Especially for dark sector masses in the 10 MeV-10 GeV range, the most promising signals are electron scattering events pointing toward the galactic center. These can be detected in experiments designed for neutrino physics or proton decay, in particular Super-K and its upgrade Hyper-K, as well as the PINGU/MICA extensions of IceCube. This boosted DM phenomenon highlights the distinctive signatures possible from non-minimal dark sectors. ©2014
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it