Self-organization and control in stimulated Raman backscattering
Bibliographic record
Abstract
Abstract A stimulated Raman scattering (SRS) on electron plasma waves in underdense plasmas is of a big concern in laser fusion due to an energy loss and target preheating. Complex features of large Backward-SRS (BRS) in experiments and simulations with laser fusion targets are found. Recently, to reach ultra-high intensities at multi-exawatts and beyond, relevant to high-energy physics, Raman amplification based on BRS was proposed; still, with high sensitivity and a narrow operational window. Firstly, we revisit a standard three-coupled mode model of BRS to show that the condition for an absolute instability is readily satisfied in uniform plasmas which excites large Raman signals from a background noise. It sets in for interaction length L0 shorter than, both, the plasma length L and absorption length La. Further, we point out a generic BRS feature, which due to a nonlinear frequency shift in large electron plasma wave (relativistic/trapping effects), instead to a steady state, saturates via intermittent pulsations with incoherent spectral broadening. A ‘break up’ of Manley–Rowe invariants is shown to predict non-stationary BRS. Finally, an intermediate intensity regime is originally proposed for coherent femto-second pulse generation in a thin exploding foil plasma, with scalings investigated by theory and particle simulations.
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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 | 0.001 |
| 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 | 0.001 | 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".