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Record W2360214500

Nonlinear propagation of localized wavefront deformation in high-power laser facility

2006· article· en· W2360214500 on OpenAlexaff
Hongjie Liu, Jing Feng, Yanlei Zuo, Xiaofeng Wei, Hu Dongxia, Zhitao Peng, Qiang Li, Zhou Wei, Kun Zhang, Lei Jiang, Zhijun Li, Zuo Ming

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Systems and Laser Technology
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsWavefrontOpticsPhysicsAmplitudeWavefront sensorDeformable mirrorBeam (structure)LaserRippleDeformation (meteorology)Nonlinear systemAdaptive opticsPower (physics)
DOInot available

Abstract

fetched live from OpenAlex

A theory model which describes the localized wavefront deformation of the optics elements is set up.The propagation regularity of the high-power plane-wave in the optics elements with localized wavefront deformation is investigated by linearization method of the ripple propagation.A continuous laser medium as an example is simulated with the model,and the spectral distribution clue to the localized wavefront deformation with different scales,the nonlinear gain of the amplitude clue to wave-front ripple with differen frequency,the relationship between the nonlinear gain and the beam transmission distance in the case of different B integral,the transmission distance where there exists the largest nonlinear gain of the output beam amplitude,and the amplitude distribution by the localized wavefront deformation are obtained.The simulation results show that to avoid damaging the optics it is nccessary to prevent the flaws from coming into being of 0.5~2.0 mm in radius on the surface of the optics.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.004
GPT teacher head0.177
Teacher spread0.173 · 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 designSimulation or modeling
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

Citations2
Published2006
Admission routes1
Has abstractyes

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