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Record W2729599614 · doi:10.1364/ol.43.003622

On-chip silicon photonic integrated frequency-tunable bandpass microwave photonic filter

2018· article· en· W2729599614 on OpenAlexafffund

Bibliographic record

VenueOptics Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBand-pass filterPassbandPhotonicsPhase modulationResonatorOptical filterFree spectral rangePhotodetectorModulation (music)Microwave

Abstract

fetched live from OpenAlex

An on-chip frequency-tunable bandpass microwave photonic filter (MPF) implemented on a silicon photonic platform is reported. The on-chip MPF consists of a high-speed phase modulator (PM), a thermally tunable high-Q micro-disk resonator (MDR), and a high-speed photodetector (PD). The filtering function of the MPF is realized based on phase modulation and phase modulation to intensity modulation conversion, to translate the spectral response of the MDR in the optical domain to the spectral response of the MPF in the microwave domain. The tunability of the MPF is realized by thermally tuning the MDR. The proposed on-chip bandpass MPF is fabricated and characterized. An MPF with a passband of 1.93 GHz and a tunable range from 3 to 10 GHz is demonstrated. The power consumption, the insertion loss, and the bandwidth over the entire tunable range are studied. This successful implementation of an MPF marks a significant step forward in the full integration of microwave photonic systems on a single chip.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations83
Published2018
Admission routes2
Has abstractyes

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