Effect of nonextensive electrons on dust–ion acoustic wave self-modulation
Bibliographic record
Abstract
Nonlinear self-modulation of dust–ion acoustic (DIA) waves is studied in an unmagnetized dusty plasma comprising warm adiabatic ions, arbitrarily charged dust particles, and hot nonextensive q-distributed electrons. By employing the multiple space and time scales perturbation, a nonlinear Schrödinger equation is derived for the evolution of the wave amplitude. The existence along with the stability of wave packets are discussed in the parameter space of two oppositely charged dust and ion temperature over different ranges of the nonextensive parameter q. The growth rate of the modulation instability is also given for different values of the q parameter. It is found that the critical wave number at which the instability sets in increases as the nonextensive parameter q increases. This leads to a wider range (in spatial extension) of the stable envelope solitons. It is also found that the effects of ion temperature and negative (positive) dust concentration significantly modify the criteria for the modulation instability of DIA waves. Our finding should elucidate the nonlinear electrostatic structures that propagate in astrophysical and cosmological plasma scenarios where nonextensive particles exist: such as instellar plasma, stellar polytropes, cosmic radiation, and systems with long-rang interaction.
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 | 0.001 |
| 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".