Evolution of the stimulated Raman scattering instability in two-dimensional particle-in-cell simulations
Bibliographic record
Abstract
In the following work, we analyze one-dimensional (1D) and two-dimensional (2D) full particle-in-cell simulations of stimulated Raman scattering (SRS) and study the evolution of Langmuir waves (LWs) in the kinetic regime. It is found that SRS reflectivity becomes random due to a nonlinear frequency shift and that the transverse modulations of LWs are induced by (i) the Weibel instability due to the current of trapped particles and (ii) the trapped particle modulational instability (TPMI) [H. Rose, Phys. Plasmas 12, 12318 (2005)]. Comparisons between 1D and 2D cases indicate that the nonlinear frequency shift is responsible for the first saturation of SRS. After this transient interval of first saturation, 2D effects become important: a strong side-scattering of the light, caused by these transverse modulations of the LW and the presence of a nonlinear frequency shift, is observed together with a strong transverse diffusion. This leads to an increase of the Landau damping rate of the LW, contributing to the limiting of Raman backscattering. A model is developed that reproduces the transverse evolution of the magnetic field due to trapped particles. Based on a simple 1D hydrodynamic model, the growth rate for the Weibel instability of the transverse electrostatic mode and magnetic field is estimated and found to be close to the TPMI growth rate [H. Rose et al., Phys. Plasmas 15, 042311 (2008)].
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".