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Record W4394955582 · doi:10.1063/5.0185184

PIC simulations of the competition between backward and forward stimulated Raman side scatter in ignition-scale direct-drive coronal conditions

2024· article· en· W4394955582 on OpenAlexafffund
Q Wang, C. Z. Xiao, Y. Xie, Hongbo Cai, Jing Chen, Z. J. Liu, L. H. Cao, Chunyang Zheng, C. S. Liu, W. Rozmus, J. F. Myatt, X. T. He

Bibliographic record

VenuePhysics of Plasmas · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilChina Postdoctoral Science FoundationNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCompute Canada
KeywordsPhysicsNational Ignition FacilityScale (ratio)Ignition systemPlasmaCoronal planeComputational physicsMechanicsNuclear physicsThermodynamicsInertial confinement fusionMedicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.268
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2024
Admission routes2
Has abstractyes

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