Facet phases and sub-threshold spectra of DFB lasers: spectral extraction, features, explanations and verification
Bibliographic record
Abstract
The sub-threshold spectra of distributed feedback (DFB) lasers are heavily influenced by the phase of the internal grating with respect to the end facets. In this paper, we document features commonly observed in sub-threshold spectra and explain these features as manifestations of the facet phases. We extract estimates of facet phases by fitting a probability-amplitude transfer-matrix model to spectra from six truncated-well DFB lasers, and use the probability-amplitude model to document, isolate, and explain the sub-threshold spectral dependence on facet phase. To verify the accuracy of the approach that we have taken, we compare estimates of the facet phases from the fits to independent measurements of the facet phases using a scanning photoluminescence method. The results from the two methods are compared and are found to be in agreement. The agreement validates our use of the probability-amplitude model in this paper to explain laser facet phase phenomena.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".