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Record W2530114778 · doi:10.1063/1.4964724

Nonlinear excitation of long-wavelength modes in Hall plasmas

2016· article· en· W2530114778 on OpenAlexafffund
V. P. Lakhin, V. I. Ilgisonis, A. I. Smolyakov, E. A. Sorokina

Bibliographic record

VenuePhysics of Plasmas · 2016
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Saskatchewan
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of CanadaRussian Foundation for Basic Research
KeywordsPhysicsLower hybrid oscillationPlasmaInstabilityMagnetic fieldHall effectTwo-stream instabilityModulational instabilityUpper hybrid oscillationExcitationWaves in plasmasCondensed matter physicsElectronWavelengthDispersion relationElectromagnetic electron waveComputational physicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

Hall plasmas with magnetized electrons and unmagnetized ions exhibit a wide range of small scale fluctuations in the lower-hybrid frequency range as well as low-frequency large scale modes. Modulational instability of lower-hybrid frequency modes is investigated in this work for typical conditions in Hall plasma devices such as magnetrons and Hall thrusters. In these conditions, the dispersion of the waves in the lower-hybrid frequency range propagating perpendicular to the external magnetic field is due to the gradients of the magnetic field and the plasma density. It is shown that such lower-hybrid modes are unstable with respect to the secondary instability of the large scale quasimode perturbations. It is suggested that the large scale slow coherent modes observed in a number of Hall plasma devices may be explained as a result of such secondary instabilities.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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