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Record W4312082270 · doi:10.1063/5.0124468

Single-core multi-channel moiré fiber grating and multi-wavelength LMA fiber grating fabricated based on two-dimensional spatially encoded phase mask

2022· article· en· W4312082270 on OpenAlexaff
Zonglun Che, Pan Xu, Chunyan Cao, Xijia Gu, Lina Ma, Jing Zhu, Jun Wang

Bibliographic record

VenueAIP Advances · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFiber Bragg gratingOpticsMaterials scienceGraded-index fiberLong-period fiber gratingGratingPHOSFOSDispersion-shifted fiberPlastic optical fiberSingle-mode optical fiberPolarization-maintaining optical fiberCore (optical fiber)Diffraction gratingPhotonic-crystal fiberOptical fiberFiber optic sensorOptoelectronicsWavelengthPhysics

Abstract

fetched live from OpenAlex

A two-dimensional optical fiber grating with multi sub-gratings based on a 2D spatially encoded phase mask is designed in this study. The 2D fiber Bragg grating (FBG) is composed of two non-overlapping sub-FBGs, which are laterally separated along the radial direction of the fiber core. Unlike traditional FBGs, the refractive index of the 2D FBG is modulated both on the axial and radial directions of the fiber core, which are realized by spatially encoded diffraction based on a 2D spatially encoded phase mask. Compared with the overlapping grating, the 2D FBG can be fabricated at one time to achieve multi-wavelength output, and its compact structure provides a new idea for multi-wavelength multiplexing. As examples, a single-core multi-channel moiré fiber grating and 2D FBG with three subgratings are designed and fabricated on a single-mode fiber and LMA fiber, respectively. Using a 2D spatially encoded mask can improve the optical fiber refractive index modulation from one- to two- or even three-dimensions, which is helpful for precise manipulation of the complex optical field of optical fiber.

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 score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.032
GPT teacher head0.269
Teacher spread0.237 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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