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Record W4400194405 · doi:10.1364/optcon.524839

Arbitrary waveform generation system using a quantum dash optical frequency comb source

2024· article· en· W4400194405 on OpenAlexafffund
Yuxuan Xie, Mostafa Khalil, Touline Erfan, Jiaren Liu, Zhenguo Lü, Philip J. Poole, John Weber, Guocheng Liu, Mohamed Rahim, Lawrence R. Chen

Bibliographic record

VenueOptics Continuum · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsWaveformComb filterPhysicsAcousticsArbitrary waveform generatorSine waveFilter (signal processing)OpticsComputer scienceElectronic engineeringBandwidth (computing)TelecommunicationsEngineeringRadar

Abstract

fetched live from OpenAlex

We present an approach for microwave photonic (MWP) arbitrary waveform generation utilizing a quantum dash optical frequency comb source. Leveraging the availability of up to 41 comb lines and incorporating a real-time control feedback loop for precise comb shaping, we design a suite of MWP filters. Through the introduction of an ultra-short RF train, we obtain the impulse responses of the MWP filters, facilitating the construction of a versatile MWP arbitrary waveform generation system. In this study, we showcase the generation of rectangular, triangular, and sine burst waveforms. We can achieve an accuracy exceeding 90% in our generated waveform compared to the target waveform. Additionally, we demonstrate the tunability of the pulse width of rectangular and triangular waveforms, ranging from 0.62 ns to 4.56 ns, along with the adjustability of the triangular waveform slope. By manipulating the delay of the MWP filter, our system can also generate sine bursts, periodic sinusoids, and sinusoids with envelopes, with clock frequencies lower than that of the sinusoid itself.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.254
Teacher spread0.234 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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