Delay drift compensation of an optoelectronic oscillator over a large temperature range through continuous tuning
Bibliographic record
Abstract
Phase noise reduces target sensitivity in radar and increases bit error rate in telecommunications systems. Optoelectronic oscillators are known for using optical fibre technology to realise the large delay required to attain superior phase noise performance compared to conventional microwave source technology. However, the long fibre is vulnerable to environmentally induced phase perturbations, while conventional phase shifters have insufficient range to compensate for the phase drift over the operational temperature range without the use of a temperature-controlled enclosure. Here we introduce a vector modulator controlled by a Stuart-Landau integrator, as a solution to non-efficient tuning for the phase shift. The concept is verified by simulation and experimentally demonstrated using an optoelectronic oscillator phase-locked to a system reference. Phase lock is maintained over four free spectral ranges equivalent to a tuning phase range of 1440° when the optoelectronic oscillator is cycled over a 10 °C to 85 °C temperature range. These demonstrations highlight the practical potential of our continuous tuning method.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".