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Record W4401338827 · doi:10.1002/apxr.202400034

Advanced Modeling of Electro‐Optic Sampling: Nonlinear Vectoral‐Field Solutions to Maxwell's Equations

2024· article· en· W4401338827 on OpenAlexafffund
B. N. Carnio, Oussama Moutanabbir, A. Y. Elezzabi

Bibliographic record

VenueAdvanced Physics Research · 2024
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsPolytechnique MontréalUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSampling (signal processing)Terahertz radiationNonlinear systemElectric fieldNonlinear opticsField (mathematics)WaveguideComputer scienceNonlinear opticalOpticsMaterials sciencePhysicsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract A comprehensive modeling approach for elucidating the intricacies of electro‐optic (EO) sampling is presented, which fully encapsulates the EO sampling process by accounting for all linear and second‐order nonlinear optical effects. The developed approach implements a multi‐step procedure, involving a vectorial‐field modeling of the second‐order nonlinear interactions occurring within the EO crystal, followed by a theoretical evaluation of the subsequent optical EO sampling components. To assess the efficacy of the approach, it is used for the sampling of terahertz electric fields (<1–>60 THz) within the bulk crystals of ZnTe and LiNbO 3 , as well as a ZnTe‐based waveguide. Nonetheless, this versatile method enables the investigation of EO sampling within any crystal incorporated within any geometry. This model provides a powerful tool for the in‐depth exploration of EO sampling, paving the way for advancements in various applications.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.868
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.098
GPT teacher head0.399
Teacher spread0.301 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

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