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Record W2918248531 · doi:10.1117/12.2506942

Broadband photonic RF channelizer based on micro-combs

2019· article· en· W2918248531 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsBroadbandPhotonicsOptoelectronicsMaterials scienceRadio frequencyOpticsComputer scienceTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

In this paper, we first employ CMOS-compatible integrated optical combs to demonstrate a broadband RF channelizer. By using an on-chip nonlinear micro-ring resonator, a broadband 200GHz-spacing Kerr comb with a large number of comb lines are generated, providing a record large number of wavelength channels (over 60 in the C- and L- band) as well as over 100GHz potential RF operation bandwidth for RF channelizers with greatly reduced size, potential cost, and complexity. Record-high spectral slice resolution of 124.94 MHz is achieved through an on-chip MRR featuring a high Q factor up to 1.549&times;10<sup>6</sup>. As a result, broadband channelization of RF frequencies ranging from 1.7 GHz to 19 GHz is experimentally demonstrated, verifying our approach’s feasibility and effectiveness towards the realization of broadband RF channelizer with large channel number and high resolution, as well as reduced cost and footprint.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.444
Threshold uncertainty score1.000

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)0.0010.002

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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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