Microcavity In-Line Mach–Zehnder Interferometers Fabricated in Single-Mode Fibers and Fiber Tapers for Visible (VIS) and Near-Infrared (NIR) Operation
Bibliographic record
Abstract
In this paper, we analyze the performance of single-mode fiber (SMF) microcavity in-line Mach-Zehnder interferometers (μIMZI) in the visible (VIS) and near-infrared (NIR) spectral ranges. Furthermore, we study the causes leading to a seeming paradox that NIR SMFs for the VIS range perform better in the NIR range and vice versa. We propose the use of short double tapers to improve the spectral range and visibility of the micro-interferometers. The sensitivities to surrounding refractive index obtained were as high as 11,400 nm/RIU.
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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 | 0.001 | 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 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".