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Record W1559270878 · doi:10.1063/1.4921147

The scaling of electron and positron generation in intense laser-solid interactions

2015· article· en· W1559270878 on OpenAlexaff
Hui Chen, A. Link, Y. Sentoku, P. Audebert, Frederico Fiúza, A. Hazi, R. F. Heeter, M. P. Hill, L. M. R. Hobbs, A. Kemp, G. E. Kemp, S. Kerr, D. D. Meyerhofer, J. F. Myatt, S. R. Nagel, J. Park, R. Tommasini, G. J. Williams

Bibliographic record

VenuePhysics of Plasmas · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersLaboratory Directed Research and DevelopmentLawrence Livermore National LaboratoryU.S. Department of Energy
KeywordsPhysicsPositronAtomic physicsLaserScalingElectronPlasmaEnergy (signal processing)Nuclear physicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

This paper presents experimental scalings of the electrons and positrons produced by intense laser-target interactions at relativistic laser intensities (1018–1020 W cm−2). The data were acquired from three short-pulse laser facilities with laser energies ranging from 80 to 1500 J. We found a non-linear (≈EL2) scaling of positron yield [Chen et al., Phys. Rev. Lett. 114, 215001 (2015)] and a linear scaling of electron yield with the laser energy. These scalings are explained by theoretical and numerical analyses. Positron acceleration by the target sheath field is confirmed by the positron energy spectrum, which has a pronounced peak at energies near the sheath potential, as determined by the observed maximum energies of accelerated protons. The parameters of laser-produced electron-positron jets are summarized together with the theoretical energy scaling. The measured energy-squared scaling of relativistic electron-positron jets indicates the possibility to create an astrophysically relevant experimental platform with such jets using multi-kilojoule high intensity lasers currently under construction.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.285
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations46
Published2015
Admission routes1
Has abstractyes

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