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Record W4243504086 · doi:10.1063/1.3485119.1

10.1063/1.3485119.1

2010· dataset· en· W4243504086 on OpenAlexaff
X. Lavocat-Dubuis, J. P. Matte

Bibliographic record

VenueDefault Digital Object Group · 2010
Typedataset
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsGratingOpticsHarmonicsPhysicsFemtosecondAttosecondLaserHarmonicWavelengthUltrashort pulseQuantum mechanics

Abstract

fetched live from OpenAlex

The generation of harmonics by the interaction of a femtosecond, relativistic intensity laser pulse with a grating of subwavelength periodicity was studied numerically and theoretically. For normal incidence, strong, coherent emission at the wavelength of the grating period and its harmonics is obtained, nearly parallel to the target surface, due to relativistic electron bunches emanating from each protuberance. For oblique incidence (30°), only even harmonics of the grating periodicity are seen, but with an even higher intensity. This is due to constructive interference of the emission from the grating protuberances. The emission along the grating surface is composed of trains of attosecond pulses; therefore there is no need to use a filter. An efficiency greater than 10−4 is obtained for the 24th harmonic. The conversion efficiency is fairly constant when the similarity parameter S=ne/(a0nc)(∝neλL/IL1/2) is held fixed, and is optimum when S≃4. Here, ne and nc are the electron density and the critical density; a0=eEL/(meωLc) is the quiver momentum in the laser field EL normalized to mec.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.688
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.008
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.3120.594

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations3
Published2010
Admission routes1
Has abstractyes

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