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Record W2088993246 · doi:10.1364/oe.21.006873

Capturing reflected cladding modes from a fiber Bragg grating with a double-clad fiber coupler

2013· article· en· W2088993246 on OpenAlexaff
Mohamad Diaa Baiad, Mathieu Gagné, Simon Lemire-Renaud, Étienne De Montigny, Wendy‐Julie Madore, Nicolas Godbout, Caroline Boudoux, Raman Kashyap

Bibliographic record

VenueOptics Express · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCladding (metalworking)Fiber Bragg gratingMaterials scienceOpticsCladding modeLong-period fiber gratingTaperingRefractive indexGratingOptical fiberPhotonic-crystal fiberPlastic optical fiberGraded-index fiberSingle-mode optical fiberDouble-clad fiberPolarization-maintaining optical fiberOptoelectronicsFiber optic sensorPhysicsComposite materialComputer science

Abstract

fetched live from OpenAlex

We present a novel measurement scheme using a double-clad fiber coupler (DCFC) and a fiber Bragg grating (FBG) to resolve cladding modes. Direct measurement of the optical spectra and power in the cladding modes is obtained through the use of a specially designed DCFC spliced to a highly reflective FBG written into slightly etched standard photosensitive single mode fiber to match the inner cladding diameter of the DCFC. The DCFC is made by tapering and fusing two double-clad fibers (DCF) together. The device is capable of capturing backward propagating low and high order cladding modes simply and efficiently. Also, we demonstrate the capability of such a device to measure the surrounding refractive index (SRI) with an extremely high sensitivity of 69.769 ± 0.035 μW/RIU and a resolution of 1.433 × 10(-5) ± 8 × 10(-9) RIU between 1.37 and 1.45 RIU. The device provides a large SRI operating range from 1.30 to 1.45 RIU with sufficient discrimination for all individual captured cladding modes. The proposed scheme can be adapted to many different types of bend, temperature, refractive index and other evanescent wave based sensors.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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.

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

Citations9
Published2013
Admission routes1
Has abstractyes

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