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Observation of ponderomotively driven bow shock using Thomson scattering

2025· article· en· W4407430599 on OpenAlexaff
A. L. Milder, C. Bruulsema, S. Hüller, C. A. Walsh, W. Rozmus, L. Yin, Jan Ludwig, W. A. Farmer, B. J. Albright, Harvey A. Rose, G. F. Swadling

Bibliographic record

VenuePhysical Review Research · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersLos Alamos National LaboratoryNational Nuclear Security AdministrationUniversity of RochesterLawrence Livermore National LaboratoryU.S. Department of Energy
KeywordsShock (circulatory)Bow shock (aerodynamics)Thomson scatteringPhysicsScatteringMechanicsShock waveOpticsMedicine

Abstract

fetched live from OpenAlex

High-energy speckled lasers are known to exert ponderomotive forces on a plasma. This can reduce flow transverse to the propagation of the beams. When coupled with a supersonic flow, this has been shown to lead to the formation of a shock that travels against the flow. Experiments conducted on the OMEGA laser facility have used Thomson scattering to observe density and velocity changes consistent with this ponderomotively driven shock. Comparisons of the data with hydrodynamic simulations with the ponderomotive force, particle-in-cell simulations with a full Maxwell field solver, and hydrodynamic simulations without the ponderomotive force show that this shock feature is only reproduced when accounting for the ponderomotive force.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.123
GPT teacher head0.447
Teacher spread0.324 · 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 designBench or experimental
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

Citations2
Published2025
Admission routes1
Has abstractyes

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