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Record W2920155409 · doi:10.1117/12.2508641

Silicon photonic integrated circuits for microwave signal generation and processing

2019· article· en· W2920155409 on OpenAlexaff
Weifeng Zhang, Jianping Yao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhotonicsMicrowaveSignal processingElectronic engineeringPhase noiseRadarBand-pass filterOptical filterComputer sciencePhotonic integrated circuitMicrowave engineeringWirelessSIGNAL (programming language)Filter (signal processing)Digital signal processingElectrical engineeringOptoelectronicsEngineeringMaterials scienceTelecommunications

Abstract

fetched live from OpenAlex

High-frequency microwave signal generation and processing are highly needed in future multi-functional radar and nextgeneration wireless communication systems. It is extremely difficult or impossible for electronics to fulfil the tasks. As an enabling technology, photonics has been considered a promising solution for the generation and processing of highfrequency microwave signals. In this paper, photonic integrated solutions for microwave signal generation and processing will be discussed. Specifically, a monolithically integrated silicon-photonic frequency-tunable microwave bandpass filter and a frequency-tunable low phase-noise optoelectronic oscillator are discussed. This successful demonstration of the two integrated microwave photonic systems marks a significant step forward for large-scale implementation of integrated microwave photonic systems for future radar and wireless communication applications.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.385

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)0.0000.000

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 head0.241
Teacher spread0.219 · 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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

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