Fiber guided mode dispersion spectroscopy via control of spatial dimensions
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Bibliographic record
Abstract
The development of next-generation optical fiber grating devices is strongly influenced by intricate grating design, which must effectively capture guided mode dispersion. Understanding this dispersion is crucial for enhancing measurement accuracy in dispersion compensation, guided mode phase matching for nonlinear frequency conversion, and optical sensing. However, higher-order guided modes remain challenging to interpret due to limited experimental validation. In this study, we present tilted fiber Bragg grating based mode dispersion spectroscopy that allows for real-time tracking of high order guided mode (∼50th order) dispersion as a function of fiber diameter and wavelength. As fiber diameter reduces, all guided mode resonances shift to shorter wavelength, the separation between resonances associated with even and odd azimuthal order increases, and single resonances split into multiple peaks relying on polarization effects and coupling efficiency. Simulations based on coupled-mode theory corroborate these findings, revealing that with reduced fiber diameter, the azimuthal mode order contribute to such unexpected resonance splitting. This investigation represents a significant step forward, offering new insights into high order guided mode dispersion calibration and demonstrating how grating can refine existing models for predicting and controlling the mode dispersion.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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