Effect of superthermal electrons on the characteristics of dust acoustic solitary waves in a magnetized hot dusty plasma with dust charge fluctuation
Bibliographic record
Abstract
A nonlinear dust acoustic solitary wave (DASW) in a magnetized dusty plasma with superthermal electrons is studied analytically. In this model hot electrons are described by the kappa distribution function, but ions are taken to be Maxwellian and plasma pressure and dust-natural collisions have been taken into account. Using the reductive perturbation method the Zakharov–Kuznetsov equation is derived and effect of electrons’ hotness on the amplitude and width of soliton in dusty plasma is investigated. With decreasing energy of the hot electrons in the system, κ > 100, results coincide with the results of the dusty plasma system containing Maxwellian electrons. In this model anisotropy is caused by an external magnetic field while inhomogeneity is generated by ion density gradient in the plasma. The initial density decreases exponentially in the space along one direction. The amplitude of DASW is mainly affected by density inhomogenity rather than the electrons’ energy. With increasing energy of the system, the width of DASW increases significantly. Applying the effect of pressure in the model only rarefactive DASW may be generated in the dusty plasma.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".