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Deterministic-Frequency Optoelectronic Synthesizer Architecture Using Injection-Locked Oscillators

2025· article· W7130590467 on OpenAlexaff
Basel Chihabi, Jim Wight, Rony E. Amaya

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsPhase noiseRadio frequencyFrequency synthesizerLocal oscillatorNoise (video)RadarPhase (matter)Photonics

Abstract

fetched live from OpenAlex

Optoelectronic oscillators (OEOs) are widely used in high-precision radiofrequency (RF) signal generation due to their ultra-low phase noise characteristics. However, conventional OEOs suffer from unpredictable startup frequencies, leading to inconsistencies in practical applications. Conversely, traditional RF oscillators exhibit deterministic startup frequencies but are inherently limited by higher phase noise. This paper presents a novel OEO architecture that integrates an RF injection-locked oscillator (ILO) to overcome both challenges simultaneously. By leveraging the frequency-selective properties of the ILO, the proposed system ensures that the OEO consistently starts at a predefined frequency while maintaining its ultra-low phase noise. This advancement is critical for applications in high-precision timing, stable RF communications, and next-generation radar and sensing systems, where both frequency stability and spectral purity are paramount. Experimental results demonstrate that the proposed approach effectively locks the startup frequency with high precision while preserving the superior phase noise performance of the OEO. This breakthrough paves the way for more robust and reliable frequency-selective systems in advanced RF and photonic technologies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.272
Teacher spread0.261 · 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.

Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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