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Record W4415808822 · doi:10.1063/5.0250501

Electrostatic waves in the maximum-entropy fluid model: Longitudinal electron modes

2025· article· en· W4415808822 on OpenAlexaff
Stefano Boccelli, Rostislav‐Paul Wilhelm, James G. McDonald, Manuel Torrilhon

Bibliographic record

VenuePhysics of Plasmas · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Ottawa
FundersGoddard Space Flight CenterBundesministerium für Bildung und ForschungOak Ridge Associated UniversitiesNational Aeronautics and Space Administration
KeywordsKinetic energyDispersion relationInstabilityMoment (physics)ElectronPlasmaVlasov equationDispersion (optics)Kinetic theory

Abstract

fetched live from OpenAlex

Traditional fluid models are unable to reproduce the kinetic dispersion relation of certain plasma waves and the onset of kinetic instabilities. Non-equilibrium fluid models (higher-order moment methods) permit to reproduce selected kinetic effects, but at a lower computational cost as compared to fully-kinetic models. In this work, we study the dispersion relation of longitudinal electrostatic electron modes. We show that the fourth-order maximum-entropy moment method is able to recover certain kinetic instabilities, although with a slightly increased region of stability if compared to the Vlasov equation. As in the kinetic-theory case, these instabilities appear when the gas is in a non-equilibrium state that is associated with a sufficiently bi-modal VDF. The maximum-entropy method is able to predict the classical two-stream instability within a single-fluid formulation, reproducing a reasonably accurate growth rate. The Vlasov-stability of maximum-entropy VDFs is also investigated via Nyquist diagrams and the Penrose criterion.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.984

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 integrity0.0000.000
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 head0.282
Teacher spread0.267 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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