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Record W2072994635 · doi:10.1063/1.3514595

Single-shot divergence measurements of a laser-generated relativistic electron beam

2010· article· en· W2072994635 on OpenAlexaff
F. Pérez, S. D. Baton, C. D. Chen, D. Hey, M. H. Key, S. Le Pape, T. Ma, H. S. McLean, A. G. MacPhee, P. K. Patel, F. N. Beg, D. P. Higginson, Christopher W. Murphy, Hiroshi Sawada, B. Westover, T. Yabuuchi, K. U. Akli, E. Giraldez, M. Hoppe, Catherine Shearer, R. B. Stephens, L. Grémillet, Éric Lefebvre, R. R. Freeman, G. E. Kemp, A. Krygier, L. D. Van Woerkom, R. Fedosejevs, R. H. Friesen, Ying Y. Tsui, D. Turnbull

Bibliographic record

VenuePhysics of Plasmas · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersLawrence Livermore National LaboratoryU.S. Department of Energy
KeywordsPhysicsDivergence (linguistics)ElectronBeam (structure)Relativistic electron beamPicosecondCathode rayBeam divergenceMonte Carlo methodOpticsLaserAtomic physicsPlasmaShot (pellet)Computational physicsLaser beam qualityLaser beamsNuclear physics

Abstract

fetched live from OpenAlex

The relativistic electron transport induced by an ultraintense picosecond laser is experimentally investigated using an x-ray two-dimensional imaging system. Previous studies of the electron beam divergence [R. B. Stephens et al. Phys. Rev. E 69, 066414 (2004), for instance] were based on an x-ray imaging of a fluorescence layer buried at different depths in the target along the propagation axis. This technique required several shots to be able to deduce the divergence of the beam. Other experiments produced single-shot images in a one-dimensional geometry. The present paper describes a new target design producing a single-shot, two-dimensional image of the electrons propagating in the target. Several characteristics of the electron beam are extracted and discussed and Monte Carlo simulations provide a good understanding of the observed beam shape. The proposed design has proven to be efficient, reliable, and promising for further similar studies.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.707

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 head0.037
GPT teacher head0.265
Teacher spread0.228 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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