Approach for Temperature-Sensitivity Enhancement in a Tapered Dual-Core As<sub>2</sub>Se<sub>3</sub>-PMMA Fiber With an Antisymmetric Long-Period Grating
Bibliographic record
Abstract
We propose and demonstrate an approach for temperature-sensitivity enhancement based on effective group-velocity matching between the even and odd modes of a dual-core As <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Se <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> -PMMA fiber taper on which an antisymmetric long-period grating is inscribed. The transmission of optical pulses in the dual-core As <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Se <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> -PMMA taper inscribes the antisymmetric long-period grating that causes the electric fields to couple back and forth between the even and odd modes leading to effective group-velocity matching between the two modes. The variation of the difference between phases of the two modes φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> (λ) with respect to wavelength tends to 0 (∂φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> (λ)/∂λ → 0) near the resonance wavelength of the grating due to effective group-velocity matching between the two modes, and consequently, thermally induced change of the difference between phases of the two modes φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> (λ) leads to a large wavelength shift indicating enhancement of the temperature measurement sensitivity. Experimental results show that temperature measurement sensitivity in the wavelength range with effective group velocity matching is enhanced by a factor of 4.0 in comparison with the sensitivity in the wavelength range that does not have effective group velocity matching in the dual-core taper with As <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Se <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> core diameter of 1.5 μm. Exploiting sensitivity enhancement within the group-velocity matching wavelength range opens the path toward the realization of novel high-sensitivity fiber sensors for temperature and strain measurement.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".