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Record W1992386211 · doi:10.1088/2041-8205/749/2/l26

GAMMA RAYS FROM THE TYCHO SUPERNOVA REMNANT: MULTI-ZONE VERSUS SINGLE-ZONE MODELING

2012· article· en· W1992386211 on OpenAlexaff
A. M. Atoyan, C. D. Dermer

Bibliographic record

VenueThe Astrophysical Journal Letters · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsConcordia University
Fundersnot available
KeywordsPhysicsCosmic raySupernovaSupernova remnantAstrophysicsHadronFermi Gamma-ray Space TelescopeGamma rayElectronRange (aeronautics)RadiationNuclear physics

Abstract

fetched live from OpenAlex

Recent Fermi and VERITAS observations of the prototypical Type Ia supernova remnant (SNR) Tycho have discovered γ-rays with energies E in the range 0.4 GeV ≲ E ≲ 10 TeV. Crucial for the theory of Galactic cosmic-ray origin is whether the γ-rays from SNRs are produced by accelerated hadrons (protons and ions) or by relativistic electrons. Here we show that strong constraints on the leptonic model imposed in the framework of the commonly used single-zone model are essentially removed if the analysis of the broadband radiation spectrum of Tycho is done in the two-zone (or, in general, multi-zone) approach, which is likely to apply to every SNR. Importantly, we show that the single-zone approach may underpredict the γ-ray fluxes by an order of magnitude. A hadronic model can, however, also fit the detected γ-ray spectrum. The difference between γ-ray fluxes of hadronic and leptonic origins becomes significant only at ≲300 MeV, which could be revealed by spectral measurements of Tycho and other SNRs at these energies.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.032
GPT teacher head0.234
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2012
Admission routes1
Has abstractyes

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