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Record W4387908488 · doi:10.1364/ao.503919

Photonic beamforming using a quantum-dash optical frequency comb source

2023· article· en· W4387908488 on OpenAlexafffund
Yuxuan Xie, Mostafa Khalil, Hao Sun, Sehr Moosabhoy, Jiaren Liu, Zhenguo Lü, Philip J. Poole, John Weber, Lawrence R. Chen

Bibliographic record

VenueApplied Optics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsNational Research Council CanadaMcGill University
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsBeamformingFree spectral rangeBroadbandComb filterPhotonicsFrequency combPhased arrayAntenna (radio)Comb generatorPhysicsComputer scienceTelecommunicationsBandwidth (computing)Laser

Abstract

fetched live from OpenAlex

We demonstrate photonic beamforming using a quantum-dash (QD) optical frequency comb (OFC) source. Thanks to the 25 GHz free spectral range (FSR) and up to 40 comb lines available from the QD OFC, we can implement phased antenna arrays (PAAs) with directional radiation and scanning. We consider two types of PAAs: a uniform linear array (ULA) and a uniform planar array (UPA). By selecting different comb lines with a programmable optical filter, we can tune the FSR of the OFC source and realize a discrete scanning function. We evaluate the beam squint of the ULAs, and the results show that we can achieve broadband operation. Finally, we show that we can achieve both directional radiation and scanning simultaneously using the UPA.

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.264
Teacher spread0.243 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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