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Record W2133396097 · doi:10.1017/s026303460800027x

Extending the capabilities of ablation harmonics to shorter wavelengths and higher intensity

2008· article· en· W2133396097 on OpenAlexaff
T. Ozaki, L. Elouga Bom, R. A. Ganeev

Bibliographic record

VenueLaser and Particle Beams · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsHarmonicsLaserOpticsPlasmaMonochromatic colorHigh harmonic generationWavelengthHarmonicPhysicsPhoton energyMaterials scienceChirpAtomic physicsLaser ablationPhotonVoltage

Abstract

fetched live from OpenAlex

Abstract We study the generation of high-order harmonics from plasma plume, by using the 20 TW, 10 Hz laser of the Advanced Laser Light Source (ALLS). We perform detailed studies on enhancement of single high-order harmonics generated in laser plasma using the fundamental and second harmonic of the ALLS beam line. Quasi-monochromatic harmonics are observed for Mn, Cr, Sb, Sn, and In plasmas. We identify most of the ionic/neutral transitions responsible for the enhancement, which all have strong oscillator strengths. Intensity enhancements of the 13th, 17th, 21st, 29th, and 33rd harmonics from these targets are demonstrated using the 800 nm pump laser and varying its chirp. We also observed harmonic enhancement from some targets for 400 nm pump laser. Using Mn plume, we demonstrated the highest harmonic photon energy (52.9 eV) at which enhancement has been observed (17th order, λ = 23.5 nm).

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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