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Record W1576454739 · doi:10.5772/12845

Numerical Simulation of the Bump-on-Tail Instability

2011· book-chapter· en· W1576454739 on OpenAlexafffund
M. Shoucri

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsHydro-Québec
FundersHydro-Québec
KeywordsInstabilityMechanicsPhysics

Abstract

fetched live from OpenAlex

Wave-particle interaction is among the most important and extensively studied problems in plasma physics. Langmuir waves and their Landau damping or growth are fundamental examples of wave-particle interaction. The bump-on-tail instability is an example of wave growth and is one of the most fundamental and basic instabilities in plasma physics. When the bump in the tail of the distribution function presents a positive slope, a wave perturbation whose phase velocity lies along the positive slope of the distribution function becomes unstable. The bump-on-tail instability has been generally studied analytically and numerically under various approximations, either assuming a cold beam, or the presence of a single wave, or assuming conditions where the beam density is weak so that the unstable wave representing the collective oscillations of the bulk particles exhibits a small growth and can be considered as essentially of slowly varying amplitude in an envelope approximation (see for instance Umeda et al., 2003, Doveil et al. 2001, and references therein). Some early numerical simulations have studied the growth, saturation and stabilization mechanism for the beam-plasma instability (Dawson and Shanny, 1968, Denavit and Kruer, 1971, Joyce et al., 1971, Nuhrenberg, 1971). Using Eulerian codes for the solution of the Vlasov-Poisson system (Cheng and Knorr, 1976, Gagne and Shoucri, 1977), it has been possible to present a better picture of the nonlinear evolution of the bump-on-tail instability (Shoucri, 1979), where it has been shown that for a single wave perturbation the initial bump in the tail of the distribution is distorted during the instability, and evolves to an asymptotic state having another bump in the tail of the spatially averaged distribution function, with a minimum of zero slope at the phase velocity of the initially unstable wave (in this way the large amplitude wave can oscillate at constant amplitude without growth or damping). The phase-space in this case shows in the asymptotic state a Bernstein-GreeneKruskal (BGK) vortex structure traveling at the phase-velocity of the wave (Bernstein et al., 1957, Bertrand et al., 1988, Buchanan and Dorning, 1995). These results are also confirmed in several simulations (see for instance Nakamura and Yabe, 1999, Crouseilles et al., 2009). Since the early work of Berk and Roberts, 1967, the existence of steady-state phase-space holes in plasmas has been discussed in several publications. A discussion on the formation and dynamics of coherent structures involving phase-space holes in plasmas has been presented for instance in the recent works of Schamel, 2000, Eliasson and Shukla, 2006. There are of course situations where a single wave theory and a weak beam density do not apply. In the present Chapter, we present a study for the long-time evolution of the Vlasov-

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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.228
Teacher spread0.212 · 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

Citations2
Published2011
Admission routes2
Has abstractyes

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