On the radiation energy density in the jet of high-energy-emitting BL Lac objects and its impact on their multimessenger role
Bibliographic record
Abstract
ABSTRACT We examine the potential multimessenger role of BL Lac objects emitting at high energy (so-called HBL) focusing on the limits on the energy density of soft radiation in the jet frame, a critical parameter that regulates the proton cooling and the fragmentation of ultrahigh-energy cosmic ray nuclei possibly accelerated in the jet. We show that (under the assumption that the high-energy emission bump is dominated by inverse Compton emission) the energy density of any external soft radiation field (e.g. produced by a layer surrounding the jet or in the accretion flow) cannot be larger than few times that associated with the observed synchrotron radiation produced in the emission region. Quite interestingly, the constraint that we derive is generally stronger than the limit obtained from the condition that the source is transparent to very high-energy γ-rays. Using this constraint, we can derive a robust upper limit for the efficiency of the photopion reaction leading to the emission of PeV neutrinos, fπ ≲ 10−5, which makes HBL quite inefficient neutrino sources. For the photodisintegration of nuclei, the results are more dependent on the spectral properties of the radiation field. The photodisintegration efficiency is safely below 1 (and nuclei can escape intact) for a ‘canonical’ spectrum of the soft radiation field ∝ ν−0.5. For radiation fields characterized by a softer spectrum and extended over a large portion of the jet, the efficiency increases and for an appreciable fraction of the sources nuclei with energies above 1019 eV might suffer significant photodisintegration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".