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Record W2170361611 · doi:10.1088/1367-2630/11/2/023038

Laser acceleration of high-energy protons in variable density plasmas

2009· article· en· W2170361611 on OpenAlexaff
P. Antici, J. Fuchs, E. d’Humières, J. Robiche, E. Brambrink, S. Atzeni, A. Schiavi, Y. Sentoku, P. Audebert, H. Pépin

Bibliographic record

VenueNew Journal of Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsInstitut National de la Recherche Scientifique
FundersAgence Nationale de la Recherche
KeywordsPhysicsProtonPlasmaAtomic physicsElectronAccelerationLaserYield (engineering)Energy (signal processing)Beam (structure)Energy densityPlasma accelerationNuclear physicsOptics

Abstract

fetched live from OpenAlex

The acceleration of protons, induced by electrons generated by a short-pulse laser, is experimentally investigated when varying the density of the plasma target the laser is interacting with. The experimental results are compared with particle-in-cell (PIC) simulations for which the target conditions are inferred from hydrodynamic simulations. High-energy protons are observed only for the two extreme configurations, namely solid-density foils and near- critical-density plasmas having large gradients. Cold solid foils, however, yield the highest energy protons and best proton beam profiles. As suggested by simulations, near-critical-density plasmas could be optimized to further increase the proton energy.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.350

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 head0.012
GPT teacher head0.242
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations31
Published2009
Admission routes1
Has abstractyes

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