Real-time ultrawide-band group delay profile monitoring through low-noise incoherent temporal interferometry
Bibliographic record
Abstract
A simple, highly accurate measurement technique for real-time monitoring of the group delay (GD) profiles of photonic dispersive devices over ultra-broad spectral bandwidths (e.g. an entire communication wavelength band) is demonstrated. The technique is based on time-domain self-interference of an incoherent light pulse after linear propagation through the device under test, providing a measurement wavelength range as wide as the source spectral bandwidth. Significant enhancement in the signal-to-noise ratio of the self-interference signal has been observed by use of a relatively low-noise incoherent light source as compared with the theoretical estimate for a white-noise light source. This fact combined with the use of balanced photo-detection has allowed us to significantly reduce the number of profiles that need to be averaged to reach a targeted GD measurement accuracy, thus achieving reconstruction of the device GD profile in real time. We report highly-accurate monitoring of (i) the group-delay ripple (GDR) profile of a 10-m long chirped fiber Bragg grating over the full C band (~42 nm), and (ii) the group velocity dispersion (GVD) and dispersion slope (DS) profiles of a ~2-km long dispersion compensating fiber module over an ~72-nm wavelength range, both captured at a 15 frames/s video rate update, with demonstrated standard deviations in the captured GD profiles as low as ~1.6 ps.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".