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Record W1997806823 · doi:10.1063/1.2430518

Electron beam-plasma interaction: Linear theory and Vlasov-Poisson simulations

2007· article· en· W1997806823 on OpenAlexaff
I. Silin, R. D. Sydora, K. Sauer

Bibliographic record

VenuePhysics of Plasmas · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysicsWave packetElectronDispersion relationAtomic physicsVlasov equationPlasmaPhase velocityPlasma oscillationExcited stateWavelengthBeam (structure)Superposition principleRelativistic electron beamElectromagnetic electron waveComputational physicsCathode rayCondensed matter physicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

The problem of a weak (nb∕ne∼10−3) electron beam interaction with plasma is investigated by means of linear dispersion theory and electrostatic Vlasov simulations. In the case of a warm electron beam only Langmuir-type modes in a finite wavelength band are excited. Cold beams undergo rapid heating, after which the long-wavelength Langmuir and electron-acoustic modes are damped. As the waves decelerate and heat the beam, new modes with larger wave numbers and smaller phase velocities are excited, while the fastest-growing modes saturate at a finite level. The superposition of these modes with frequencies near electron plasma frequency ωpe and broad k spectrum results in long quasiregular wave packets. The wave packets propagate slowly with group velocities typically 30 times smaller than the phase velocities and are weakly damped by the background electrons.

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)0.005
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 score0.025
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.011
GPT teacher head0.285
Teacher spread0.274 · 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

Citations26
Published2007
Admission routes1
Has abstractyes

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