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Record W2790667955 · doi:10.1117/12.2290736

Fabrication and characterization of all-fiber 120-degree optical hybrids (Conference Presentation)

2018· article· en· W2790667955 on OpenAlexaff
Marie-Hélène Bussières-Hersir, Nicolas Godbout

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTaperingMaterials scienceEquilateral triangleOpticsFabricationOptical fiberWavelengthPhase (matter)Fusion splicingOptoelectronicsPhysicsComputer scienceMathematics

Abstract

fetched live from OpenAlex

Optical hybrids enable the unambiguous measurement of both the amplitude of an optical signal and its phase relative to a reference. A fusion-tapering technique is used to produce monolithic all-fiber 3x3 optical hybrids. By a symmetry argument, theory predicts that an equilateral triangular 3x3 coupler must form a 120° hybrid whenever a power equipartition is obtained during tapering. Precision-machined holding clamps constrain three SMF-28 fibers to an equilateral triangle geometry. An oxygen-propane micro-torch is used for the fusion and tapering steps. Fabricated devices are characterized with respect to insertion loss and relative phases at different wavelengths. Fabricated devices exhibit excess loss less than 1 dB from 1300 to 1600 nm, the coupling ratio is 33,2 ± 2,6% at 1550 nm, the design center wavelength. The relative phases are measured within 120 ± 10° and 240° ± 10° across the whole C-band from 1530 to 1565 nm. Compared to previous work, all-fibre hybrids are fabricated without an outer glass tube, exhibit lower excess loss and good phase tolerance over the whole C-band.

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 score0.349
Threshold uncertainty score0.740

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)0.0010.000

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 head0.035
GPT teacher head0.250
Teacher spread0.215 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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