Characterizing short dispersion-length fiber via dispersive virtual reference interferometry
Bibliographic record
Abstract
The ability to characterize fibers with near-zero dispersion-length products is of considerable practical interest. We introduce dispersive virtual reference interferometry (DVRI) as a technique for the characterization of short length (<1m) fibers with near-zero disperison-length. DVRI has an accuracy equivalent to standard balanced spectral interferometry (on the order of 10(−3) ps and 10(−5) ps/nm for the group delay and dispersion-length measurements respectively) but does not require wide spectral bandwidths or multiple spectral scans. Following experimental validation, the DVRI technique is used to characterize a 23.3-cm erbium-doped gain fiber (dispersion-length product <0.002 ps/nm), using a tunable laser with a bandwidth of 145 nm. Furthermore, the dispersion in a 28.6-cm commercial dispersion shifted fiber is characterized across the zero-dispersion wavelength and the zero-disperison-wavelength and slope were determined to be 1566.7 nm and 8.57 × 10(−5) ps/(nm2∙m) with a precision of ± 0.2 nm and ± 0.06 × 10(−5) ps/(nm2∙m), respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".