MétaCan
Menu
Back to cohort
Record W2022640483 · doi:10.1103/physreve.73.016404

Excitation of Mach cones and energy dissipation by charged particles moving over two-dimensional strongly coupled dusty plasmas

2006· article· en· W2022640483 on OpenAlexaff
Ke Jiang, Lu-Jing Hou, You‐Nian Wang, Z. L. Mišković

Bibliographic record

VenuePhysical Review E · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDusty plasmaDissipationPlasmaPhysicsCharged particleMach numberExcited stateAtomic physicsExcitationCoupling parameterParticle (ecology)Plasma parametersCoupling (piping)MechanicsIonMaterials scienceQuantum mechanics

Abstract

fetched live from OpenAlex

We present a theoretical model for studying the interactions of charged particles with two-dimensional strongly coupled dusty plasmas, based on the quasilocalized charge approximation in which the static pair distribution function of a dust layer is determined from a molecular dynamics simulation. General expressions are derived for the perturbed dust-layer density, the induced potential in plasma, and the energy loss of a charged particle moving parallel to the dust layer. Numerical results show that the structure of Mach cones, excited in the dust layer by the charged particle, strongly depends on the plasma parameters such as the coupling parameter, the screening parameter, and the discharge pressure, as well as on the particle speed. In addition, it is found that the energy dissipation suffered by slow charged particles can be significantly enhanced in strongly coupled dusty plasmas when compared to the dissipation in weakly coupled plasmas.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.009
GPT teacher head0.265
Teacher spread0.255 · 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

Citations20
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Review ESame topicDust and Plasma Wave PhenomenaFrench-language works237,207