THE CONTRIBUTION OF FERMI-2LAC BLAZARS TO DIFFUSE TEV–PEV NEUTRINO FLUX
Bibliographic record
Abstract
ABSTRACT The recent discovery of a diffuse cosmic neutrino flux extending up to PeV energies raises the question of which astrophysical sources generate this signal. Blazars are one class of extragalactic sources which may produce such high-energy neutrinos. We present a likelihood analysis searching for cumulative neutrino emission from blazars in the 2nd Fermi -LAT AGN catalog (2LAC) using IceCube neutrino data set 2009-12, which was optimized for the detection of individual sources. In contrast to those in previous searches with IceCube, the populations investigated contain up to hundreds of sources, the largest one being the entire blazar sample in the 2LAC catalog. No significant excess is observed, and upper limits for the cumulative flux from these populations are obtained. These constrain the maximum contribution of 2LAC blazars to the observed astrophysical neutrino flux to 27% or less between around 10 TeV and 2 PeV, assuming the equipartition of flavors on Earth and a single power-law spectrum with a spectral index of −2.5. We can still exclude the fact that 2LAC blazars (and their subpopulations) emit more than 50% of the observed neutrinos up to a spectral index as hard as −2.2 in the same energy range. Our result takes into account the fact that the neutrino source count distribution is unknown, and it does not assume strict proportionality of the neutrino flux to the measured 2LAC γ -ray signal for each source. Additionally, we constrain recent models for neutrino emission by blazars.
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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 | 0.002 |
| 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 | 0.001 |
| 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".