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Fusion of regularized femtosecond filaments in air: far field on-axis emission

2016· article· en· W2531310095 on OpenAlexaff
D. E. Shipilo, N. A. Panov, E. S. Sunchugasheva, D. V. Mokrousova, V.A. Andreeva, O.G. Kosareva, Л. В. Селезнев, A. B. Savel’ev, А. А. Ионин, S. L. Chin

Bibliographic record

VenueLaser Physics Letters · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFemtosecondFusionMaterials scienceNear and far fieldField (mathematics)OpticsPhysicsLaserMathematics

Abstract

fetched live from OpenAlex

Abstract The fusion of several coherent 800 nm femtosecond filaments is induced experimentally and numerically by transmitting a beam through a mask with circular apertures followed by the focusing lens. The far-field image of the four-filament fusion region reveals bright on-axis maximum and differs drastically from the diffraction pattern of a low energy beam propagating through the mask in the linear regime. In 3 D +time numerical simulations with the carrier wave resolved we show a factor-of-5 saturable growth in the peak plasma density with successive increase in the number of mask openings. An overall spectral blueshift of the fundamental and the third harmonics follows the plasma density increase. The simulated far-field on-axis emission agrees with the experiment and serves as the indication of nonlinear interaction in the fusion region.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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