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Record W4210297892 · doi:10.1364/ol.451185

Reconfigurable microwave photonic filter based on a quantum dash mode-locked laser

2022· article· en· W4210297892 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsNational Research Council CanadaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFree spectral rangeBandwidth (computing)LaserOptical filterComb filterPhotonicsFilter (signal processing)MicrowaveFrequency comb

Abstract

fetched live from OpenAlex

We demonstrate a reconfigurable microwave photonic (MWP) filter using a quantum dash (QDash) mode-locked laser (MLL) that can generate an optical frequency comb (OFC) with ∼50 comb lines and a free spectral range of 25 GHz. Thanks to the large number of comb lines, the MWP filter responses can be easily programmed by tailoring the OFC spectrum. We implement MWP filter responses with Gaussian, sinc, flat-top, and multiple peaks, as well as demonstrate that tuning of the central frequency. We achieve a minimum 3 dB bandwidth of ∼100 MHz for a sinc-shaped MWP filter, while the maximum out-of-band rejection can be up to ∼30 dB with Gaussian apodization. Our results show that the QDash-MLL is a promising OFC source for developing integrated and reconfigurable MWP filters.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.987

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 integrity0.0000.001
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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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