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Record W2744728018 · doi:10.1103/physrevd.98.022009

Measurement of the iron spectrum in cosmic rays by VERITAS

2018· article· en· W2744728018 on OpenAlexafffund
A. Archer, W. Benbow, R. Bird, Robert Brose, M. Buchovecky, V. Bugaev, M. P. Connolly, Wei Cui, M. K. Daniel, A. Falcone, Q. Feng, J. P. Finley, Henrike Fleischhack, L. Fortson, A. Furniss, D. Hanna, O. Hervet, J. Holder, G. Hughes, T. B. Humensky, Moritz Hütten, C. A. Johnson, P. Kaaret, N. Kelley-Hoskins, D. Kieda, M. Krause, F. Krennrich, S. Kumar, M. J. Lang, G. Maier, S. McArthur, P. Moriarty, R. Mukherjee, D. Nieto, S. O’Brien, R. A. Ong, A. N. Otte, N. Park, A. Petrashyk, M. Pohl, A. Popkow, E. Pueschel, J. Quinn, K. Ragan, P. T. Reynolds, G. T. Richards, E. Roache, C. B. Rulten, I. Sadeh, J. Tyler, S. P. Wakely, O. M. Weiner, P. Wilcox, A. Wilhelm, D. A. Williams, Stephanie Wissel, B. Zitzer

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaHelmholtz Alliance for Astroparticle PhysicsU.S. Department of EnergyOffice of ScienceSmithsonian InstitutionNational Science Foundation
KeywordsCosmic rayPhysicsAstronomyAstrophysicsSpectrum (functional analysis)COSMIC cancer database

Abstract

fetched live from OpenAlex

We present a new measurement of the energy spectrum of iron nuclei in cosmic rays from 20 TeV to 500 TeV. The measurement makes use of a template-based analysis method, which, for the first time, is applied to the energy reconstruction of iron-induced air showers recorded by the VERITAS array of imaging atmospheric Cherenkov telescopes. The event selection makes use of the direct Cherenkov light which is emitted by charged particles before the first interaction, as well as other parameters related to the shape of the recorded air shower images. The measured spectrum is well described by a power law $\frac{\mathrm{d}F}{\mathrm{d}E}={f}_{0}\ifmmode\cdot\else\textperiodcentered\fi{}{(\frac{E}{{E}_{0}})}^{\ensuremath{-}\ensuremath{\gamma}}$ over the full energy range, with $\ensuremath{\gamma}=2.82\ifmmode\pm\else\textpm\fi{}0.30{(\text{stat})}_{\ensuremath{-}0.27}^{+0.24}(\text{syst})$ and ${f}_{0}=(4.82\ifmmode\pm\else\textpm\fi{}0.98{(\text{stat})}_{\ensuremath{-}2.70}^{+2.12}(\text{syst}))\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}7}\text{ }\text{ }{\mathrm{m}}^{\ensuremath{-}2}\text{ }{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{TeV}}^{\ensuremath{-}1}\text{ }{\mathrm{sr}}^{\ensuremath{-}1}$ at ${E}_{0}=50\text{ }\text{ }\mathrm{TeV}$, with no indication of a cutoff or spectral break. The measured differential flux is compatible with previous results, with improved statistical uncertainty at the highest 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.345
Teacher spread0.332 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations20
Published2018
Admission routes2
Has abstractyes

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