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Record W2013433349 · doi:10.1088/0004-637x/745/2/146

NONTHERMAL RADIATION FROM COSMIC-RAY MODIFIED SHOCKS

2012· article· en· W2013433349 on OpenAlexaff
Hyesung Kang, Paul Edmon, T. W. Jones

Bibliographic record

VenueThe Astrophysical Journal · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPhysicsCosmic rayRadiationAstrophysicsAstronomyBackground radiationCOSMIC cancer databaseSpace radiationNuclear physics

Abstract

fetched live from OpenAlex

We calculate nonthermal radiation from cosmic-ray (CR) protons and electrons accelerated at CR modified plane and spherical shocks, using time-dependent, diffusive shock acceleration (DSA) simulations that include radiative losses of CR electrons. Strong non-relativistic shocks with physical parameters relevant for young supernova remnants (SNRs) are considered in both the plane-parallel and spherically symmetric geometries, and compared at times when their dynamical and CR properties are concordant. A thermal leakage injection model and a Bohm-like diffusion coefficient are adopted. After DSA energy gains balance radiative losses, the electron spectrum at the plane shock approaches a time-asymptotic spectrum with a super-exponential cutoff above the equilibrium momentum. The postshock electron spectrum cuts off at a progressively lower momentum downstream from the shock due to the energy losses. That results in the steepening of the volume integrated electron energy spectrum by one power of the particle energy. These features evolve toward lower energies in the spherical, SNR shocks. In a CR modified shock, pion decay gamma-ray emission reveals distinct signatures of nonlinear DSA due to the concave proton momentum spectrum. Although the electron momentum spectrum has a much weaker concavity, the synchrotron spectral slope at the shock may flatten by about 0.1–0.3 between radio and X-ray bands. The slope of the volume integrated emission spectrum behaves nonlinearly around the break frequency.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations12
Published2012
Admission routes1
Has abstractyes

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