PIC simulations of the competition between backward and forward stimulated Raman side scatter in ignition-scale direct-drive coronal conditions
Bibliographic record
Abstract
The competition between forward stimulated Raman side scatter (FSRSS) and backward stimulated Raman side scatter (BSRSS) is investigated in inhomogeneous plasma using particle-in-cell (PIC) simulations. Experimental observations at the National Ignition Facility have demonstrated the significance of stimulated Raman side scatter or backscatter instability compared to two-plasmon-decay under ignition-scale conditions for various laser beam geometries. Side scatter refers to the geometry where the Raman scattered light is generated in a direction perpendicular to the local density gradient. For an obliquely incident pump, the scattered light can either copropagate (FSRSS) or counter propagate (BSRSS) with respect to the pump. Under ignition-scale conditions, linear analysis shows that both BSRSS and FSRSS are absolutely unstable (temporally growing) at higher densities (ne∼0.2 nc), whereas at lower densities (ne∼0.1 nc), BSRSS becomes convective with substantial gain, while FSRSS remains absolute. Two-dimensional PIC simulations demonstrate that the competition between BSRSS and FSRSS is sensitive to the density. BSRSS tends to dominate at higher densities, while FSRSS becomes dominant at lower densities. At moderate densities (ne∼0.15 nc), FSRSS and BSRSS coexist. Furthermore, an increase in laser intensity leads to enhanced electron trapping, which kinetically strengths and then saturates BSRSS in the lower density region.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".