Searching for High-Energy Neutrino Emission from Galaxy Clusters with IceCube
Bibliographic record
Abstract
Galaxy clusters have the potential to accelerate cosmic rays (CRs) to ultra-high energies via accretion shocks or embedded CR acceleration sites. CRs with energies below the Hillas condition will be confined within the cluster and will eventually interact with the intracluster medium (ICM) gas to produce secondary neutrinos and $γ$ rays. Using 9.5 years of muon-neutrino track events from the IceCube Neutrino Observatory, we report the results of a stacking analysis of 1094 galaxy clusters, with masses $\gtrsim 10^{14}$ \(\textup{M}_\odot\) and redshifts between 0.01 and $\sim$1, detected by the {\it Planck} mission via the Sunyaev-Zeldovich (SZ) effect. We find no evidence for significant neutrino emission and report upper limits on the cumulative unresolved neutrino flux from massive galaxy clusters after accounting for the completeness of the catalog up to a redshift of 2, assuming three different weighting scenarios for the stacking and three different power-law spectra. Weighting the sources according to mass and distance, we set upper limits at $90\%$ confidence level that constrain the flux of neutrinos from massive galaxy clusters ($\gtrsim 10^{14}$ \(\textup{M}_\odot\)) to be no more than $4.6\%$ of the diffuse IceCube observations at 100~TeV, assuming an unbroken $E^{-2.5}$ power-law spectrum.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".