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Record W4391946326 · doi:10.1109/lpt.2024.3367276

Temperature-Insensitive Tunable Optical Filter Based on a Microsphere-Coupled Off-Core Spliced Fiber

2024· article· en· W4391946326 on OpenAlexafffund
Gerard Tatel, Pedro Tovar, Élyse D’Aoust, Xiaoyi Bao

Bibliographic record

VenueIEEE Photonics Technology Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMaterials scienceMicrosphereOptical fiberCore (optical fiber)Photonic-crystal fiberOptical filterHard-clad silica optical fiberOptoelectronicsFiberPlastic optical fiberOpticsFiber optic sensorComposite materialPhysics

Abstract

fetched live from OpenAlex

A low-cost fiber-integrated temperature-insensitive tunable Fabry-Pérot filter fabricated from an off-core spliced segment of standard single mode fiber (SMF) and a commercially available barium titanate (BaTiO3) microsphere is proposed and demonstrated. The filter’s cavity extends from the cleaved face of the launching SMF to the back face of the microsphere, thus forming a hybrid (air + BaTiO3) cavity. The device is robust against temperature variations due to the null thermo-optic coefficient of air, and a self-compensating optical path effect within the microsphere enabled by diffraction optics, which is credited to its spherical structure. Indeed, the filter’s spectrum exhibits an ultra-low temperature-dependence, with experiments showing a temperature coefficient of 2 pm/°C for spectral shifts, agreeing well with theoretical calculations. Spectral contrasts higher than 35 dB were experimentally obtained, which were shown to depend on the longitudinal position of the microsphere. Such high contrasts are due to the high refractive index of the microsphere (1.9), which allows for greater reflectivity at the microsphere-air interface. Different from other off-core based filters, the one studied in this work offers wavelength tunability, which is achieved by changing the position of the microsphere either along (coarse tuning) or transversally (fine tuning) on the off-core segment. From its simplicity, low-cost, high-contrast, repeatability, temperature-independence, tunability and fiber-integration, it is expected that the proposed filter will find direct application in both research and industry.

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), Insufficient payload (model declined to judge)
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 score0.301
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.217
Teacher spread0.211 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

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