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Record W2121097464 · doi:10.1029/2004ja010793

Anomalous resistivity and the nonlinear evolution of the ion‐acoustic instability

2006· article· en· W2121097464 on OpenAlexaff
P. Petkaki, M. P. Freeman, Toby L. Kirk, C. E. J. Watt, R. B. Horne

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysicsInstabilityElectrical resistivity and conductivityElectronIonVlasov equationPlasmaNonlinear systemComputational physicsAtomic physicsStatistical physicsMechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

Collisionless magnetic reconnection requires the violation of ideal MHD by various kinetic‐scale effects whose relative importance is uncertain. Recent research has highlighted the potential importance of wave‐particle interactions by showing that Vlasov simulations of unstable ion‐acoustic waves predict an anomalous resistivity that can be at least an order of magnitude higher than a popular analytical quasi‐linear estimate. Here, we investigate the nonlinear evolution of the ion‐acoustic instability and its resulting anomalous resistivity by examining the properties of a statistical ensemble of Vlasov simulations. The simulations differ in their initial electric noise field but are otherwise identical with a Maxwellian electron‐ion plasma of low number density and low electron to ion temperature ratio, appropriate to collisionless space plasmas. By studying the evolution of an ensemble of 104 Vlasov simulations with reduced mass ratio m i / m e = 25, we show that (1) the probability distribution of anomalous resistivity values produced during the linear, quasi‐linear, and nonlinear evolution of the ion‐acoustic instability is approximately Gaussian, (2) the ensemble mean of the ion‐acoustic resistivity during the nonlinear regime is higher than estimates at quasi‐linear saturation, and (3) the ensemble standard deviation is comparable to the ensemble mean. We argue that the large variability during the nonlinear phase is due to electron and ion bounce motion which is sensitive to the initial conditions. We demonstrate that the results are essentially similar for a real mass ratio simulation.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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 designObservational
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

Citations43
Published2006
Admission routes1
Has abstractyes

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