Searches for Connections between Dark Matter and High-Energy Neutrinos with IceCube
Bibliographic record
Abstract
In this work, we present the results of searches for signatures of dark matter decay or annihilation into Standard Model particles, and secret neutrino interactions with dark matter. Neutrinos could be produced in the decay or annihilation of galactic or extragalactic dark matter. Additionally, if an interaction between dark matter and neutrinos exists then dark matter will interact with extragalactic neutrinos. In particular galactic dark matter will induce an anisotropy in the neutrino sky if this interaction is present. We use seven and a half years of the High-Energy Starting Event (HESE) sample data, which measures neutrinos in the energy range of approximately 60 TeV to 10 PeV, to study these phenomena. This all-sky event selection is dominated by extragalactic neutrinos. For dark matter of $\sim$ 1 PeV in mass, we constrain the velocity-averaged annihilation cross section to be smaller than $10^{-23}$cm$^3$/s for the exclusive $\mu^+\mu^-$ channel and $10^{-22}$ cm$^3$/s for the $b\bar b$ channel. For the same mass, we constrain the lifetime of dark matter to be larger than $10^{28}$ s for all channels studied, except for decaying exclusively to $b\bar b$ where it is bounded to be larger than $10^{27}$ s. Finally, we also search for evidence of astrophysical neutrinos scattering on galactic dark matter in two scenarios. For fermionic dark matter with a vector mediator, we constrain the dimensionless coupling associated with this interaction to be less than 0.1 for dark matter mass of 0.1 GeV and a mediator mass of $10^{-4}~$ GeV. In the case of scalar dark matter with a fermionic mediator, we constrain the coupling to be less than 0.1 for dark matter and mediator masses below 1 MeV.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".