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Record W3177091366 · doi:10.1364/ol.430834

Efficient direct mapping of the nonlinear optical response via modulated Airy beams

2021· article· en· W3177091366 on OpenAlexafffund
Pengbo Jia, J. Wu, Domenico Bongiovanni, Yi Hu, Ling Zhang, Roberto Morandotti, Zhigang Chen, Jingjun Xu

Bibliographic record

VenueOptics Letters · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Key Research and Development Program of ChinaHigher Education Discipline Innovation ProjectChina Postdoctoral Science FoundationNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsOpticsNonlinear systemAiry beamModulation (music)Spatial light modulatorBeam (structure)Laser beam qualityNonlinear opticsPhotorefractive effectPhysicsLaser beamsLaserAcoustics

Abstract

fetched live from OpenAlex

We report a scheme to achieve efficient direct mapping of the nonlinear optical response into a spatial beam profile. Compared with previous methods where a standard two-dimensional Airy beam was used as a probe, a modulated beam configuration allows for an improved mapping efficiency, stemming from the induced nonlinearity caused by the applied modulation. We find that the mapping efficiency along different orientations is highly related to the beam patterns and the type of nonlinearity. The improvement of the mapping quality and new, to the best of our knowledge, features found in simulations are further verified in experiments by testing a photorefractive nonlinearity. Our results represent a further step towards an effective tool for the direct measurement of the nonlinear optical response with low power consumption.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.262
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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 teacher head, 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

Citations3
Published2021
Admission routes2
Has abstractyes

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