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Record W2005092773 · doi:10.1364/ao.47.006625

Modified Fabry-Perot interferometric method for waveguide loss measurement

2008· article· en· W2005092773 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Optics · 2008
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOpticsFabry–Pérot interferometerInterferometryMaterials scienceLaserWaveguideBroadbandWavelengthOptical powerSemiconductor laser theoryPhysics

Abstract

fetched live from OpenAlex

An extension to the Fabry-Perot interferometric method is demonstrated to calculate the optical loss and the reflectivity for optical waveguides simultaneously. The method uses an excitation of the waveguide with a broadband amplified spontaneous emission source (a superluminescent diode in our case) and curve fitting to account for the change of input power, thereby simplifying the measurement procedure. The use of a broadband source as opposed to tunable lasers allows for simultaneous measurements over multiple wavelengths and decreased sensitivity to reflections in the cavity. Further, waveguides of different lengths are measured to calculate the optical loss and the reflectivity simultaneously. It is shown that, if the value for reflectivity is assumed, there could be a large error in the measurement of loss especially for short waveguides. Optical loss for ridge waveguides is measured and compared by using a tunable laser as the input source. The method can be used for a generic case where it is suspected that the input power changes during the measurement.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.854

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)0.0000.000

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 head0.049
GPT teacher head0.256
Teacher spread0.207 · 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