Error estimation in the analytical modeling of abrupt taper Mach-Zehnder interferometers
Bibliographic record
Abstract
In-line fiber interferometers based on abrupt tapers have been shown as a promising low-cost platform for various sensing applications. Many variations have been demonstrated experimentally using combinations and permutations of novel photonic devices such as photonic crystal fibers or multimode fibers. In this manuscript, an analytical model for light propagation in an abrupt taper Mach-Zehnder Interferometer in commercial single-mode fiber based on coupled-mode theory is detailed. The model calculates the mode propagation process, and the result is compared with previous numerical simulations. For experimental verification, an in-line Mach-Zehnder interferometer based on an abruptly tapered fiber is fabricated and tested. The spectrum calculated by the model matches well with the measured spectrum. To reduce the computational complexity, a method for step size estimation and the corresponding error accumulation is discussed and verified. This can serve as a basis to estimate the optical responses of this class of abrupt taper based fiber sensors. With the right packaging, these sensors can play a vital role in rugged and hostile environments.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".