High-Speed and High-Resolution Microwave Photonic Interrogation of a Fiber-Optic Refractometer With Plasmonic Spectral Comb
Bibliographic record
Abstract
Microwave photonic interrogation of a high-speed and high-resolution refractive index (RI) sensor based on a tilted fiber Bragg grating with surface plasmon resonance (TFBG-SPR) is proposed and experimentally demonstrated. Instead of demodulating the wavelength shift or intensity change of a TFBG-SPR spectrum in the optical domain, we convert the TFBG-SPR spectrum to the time domain based on spectral shaping (SS) and wavelength-to-time (WTT) mapping and use a digital signal processor (DSP) to extract the RI information at a high speed and high resolution. In the experiment, when an Au-coated TFBG is immersed in a solution, the TFBG-SPR spectrum will produce a dip. When the RI changes, the location of the dip in the TFBG-SPR spectrum will shift, which is a function of the RI. By passing a broadband frequency-chirped optical pulse generated by a frequency swept laser source to the TFBG-SPR and detecting the optical pulse at the output of the TFBG-SPR at a photodetector (PD), due to SS-WTT mapping, a temporal waveform with its shape identical to the optical spectrum is produced. A DSP is then used to extract the SPR envelope information from the temporal waveform. By monitoring the changes of the SPR envelope, the RI information is interrogated with a high resolution of 1.123 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> RIU at a high speed over 20 kHz.
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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) | 0.001 | 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 | 0.001 |
| 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".