Search for $$ \mathrm{U}{(1)}_{L_{\mu }-{L}_{\tau }} $$ charged dark matter with neutrino telescope
Bibliographic record
Abstract
Abstract We study a simple Dirac fermion dark matter model in $$ \mathrm{U}{(1)}_{L_{\mu }-{L}_{\tau }} $$ U1Lμ−Lτ theory. The new light gauge bosonXplays important roles in both dark matter physics and the explanation for the muong−2 anomaly. The observed dark matter relic density is realized by a large $$ \mathrm{U}{(1)}_{L_{\mu }-{L}_{\tau }} $$ U1Lμ−Lτ charge without introducing a resonance effect of theXboson. As a by-product of the model, characteristic neutrino signatures from sub-GeV dark matterψare predicted depending on the mass spectrum. We formulate the analysis of $$ \psi \overline{\psi}\to \nu \overline{\nu} $$ ψψ¯→νν¯ , and of $$ \psi \overline{\psi}\to XX $$ ψψ¯→XX followed by $$ X\to \nu \overline{\nu} $$ X→νν¯ in a model independent way. The energy spectrum of neutrinos in the former process is monochromatic while in the latter process is bowl-shape. We also evaluate sensitivity at Super-Kamiokande and future Hyper-Kamiokande detectors. The analysis is finally applied to the $$ \mathrm{U}{(1)}_{L_{\mu }-{L}_{\tau }} $$ U1Lμ−Lτ dark matter model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".