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Record W1986002430 · doi:10.1086/379156

Interpenetrating Plasma Shells: Near-Equipartition Magnetic Field Generation and Nonthermal Particle Acceleration

2003· article· en· W1986002430 on OpenAlexaff
L. O. Silva, Ricardo Fonseca, J. Tonge, J. M. Dawson, W. B. Mori, Mikhail V. Medvedev

Bibliographic record

VenueThe Astrophysical Journal · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsEquipartition theoremParticle accelerationMagnetic fieldRelativistic particlePlasmaParticle-in-cellKinetic energyParticle (ecology)AccelerationPulsarRelativistic plasmaComputational physicsAstrophysicsElectronNuclear physicsClassical mechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

We present the first three-dimensional fully kinetic electromagnetic relativistic "particle-in-cell" simulations of the collision of two interpenetrating plasma shells. The highly accurate plasma-kinetic particle-in-cell (with the total of 10 8 particles) parallel code OSIRIS has been used. Our simulations show (1) the generation of long-lived near-equipartition (electro)magnetic fields, (2) nonthermal particle acceleration, and (3) short-scale to long-scale magnetic field evolution, in the collision region. Our results provide new insights into the magnetic field generation and particle acceleration in relativistic and subrelativistic colliding streams of particles, which are present in gamma-ray bursters, supernova remnants, relativistic jets, pulsar winds, etc.

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)0.000
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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

Citations402
Published2003
Admission routes1
Has abstractyes

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