Search for neutrino emission from cores of active galactic nuclei
Bibliographic record
Abstract
The sources of the majority of the high-energy astrophysical neutrinos observed with the IceCube neutrino telescope at the South Pole are unknown. So far, only a flaring gamma-ray blazar was compellingly associated with the emission of high-energy neutrinos. However, several studies suggest that the neutrino emission from the gamma-ray blazar population only accounts for a small fraction of the total astrophysical neutrino flux. In this work we probe the production of high-energy neutrinos in the cores of active galactic nuclei (AGN), induced by accelerated cosmic rays in the accretion disk region. We present a likelihood analysis based on eight years of IceCube data, searching for a cumulative neutrino signal from three AGN samples created for this work. The neutrino emission is assumed to be proportional to the accretion disk luminosity estimated from the soft x-ray flux. Next to the observed soft x-ray flux, the objects for the three samples have been selected based on their radio emission and infrared color properties. For the largest sample in this search, an excess of high-energy neutrino events with respect to an isotropic background of atmospheric and astrophysical neutrinos is found, corresponding to a post-trial significance of $2.60\ensuremath{\sigma}$. If interpreted as a genuine signal with the assumptions of a proportionality of x-ray and neutrino fluxes and a model for the subthreshold flux distribution, then this observation implies that at 100 TeV, 27%--100% of the observed neutrinos arise from particle acceleration in the core of AGN at $1\ensuremath{\sigma}$ confidence interval.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".