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Record W2033893827 · doi:10.1364/oe.22.004006

Long-range surface plasmon triple-output Mach-Zehnder interferometers

2014· article· es· W2033893827 on OpenAlexaff
Hui Fan, Robert Charbonneau, Pierre Berini

Bibliographic record

VenueOptics Express · 2014
Typearticle
Languagees
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInterferometryOpticsMach–Zehnder interferometerAstronomical interferometerSurface plasmon polaritonCascadeSurface plasmonDynamic rangeWaveguidePhysicsMaterials sciencePower dividers and directional couplersPhase (matter)Plasmon

Abstract

fetched live from OpenAlex

A triple-output Mach-Zehnder interferometer (MZI) operating with long-range surface plasmon-polariton waves, consisting of a MZI in cascade with a triple coupler, is demonstrated at a wavelength of ~1370 nm, using the thermo-optic effect to produce phase shifting. A theoretical model for three-waveguide coupling is also proposed and was applied to compute the transfer characteristic of various designs. Dimensions for the device were selected to optimize performance, experiments were performed, and the results were compared to theory. The outputs were sinusoidally related to the thermally-induced phase shift and separated by ~2π/3 rad, as expected theoretically. Four detection schemes that take advantage of the 3 times larger dynamic range and suppress time-varying common perturbations are proposed and analyzed in order to improve the detection limit of the device. A minimum detectable phase shift ~2/3 that of a single output was obtained from a power difference scheme and a normalization scheme. The smallest minimum detectable phase shift was 7.3 mrad. The device is promising for sensing applications, including (bio)chemical sensing.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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