High-Frequency Ultrasound Sensing From Multimode Coupling in CO<sub>2</sub>-Written Long-Period Fiber Gratings
Bibliographic record
Abstract
High-frequency (> 50 MHz) ultrasound sensing requires the detection of subtle, rapid perturbations, often a small fraction of the acoustic wavelength, which can be much smaller than the optical wavelength. This leads to the associated phase shift due to ultrasound modulation to being too small to be detected using a telecom fiber-based interferometer. Structured fiber-based sensors can overcome these challenges by detecting locally induced deformations in the fiber structure inside the core. We propose a novel approach using CO<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>-written long-period fiber gratings (LPFGs), where randomly distributed micro-deformities act as amplitude gratings, eliminating the need for phase detection. Unlike commonly used UV light inscribed LPFGs, where the inscription pitch is uniform in the fiber between the periods, the wavelength of the CO<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> laser falls in the absorption band of SiO2. This causes thermal stress-induced deformations in the fiber, leading to the formation of randomly spaced Fabry-Perot (FP) cavities in the micrometer range, as demonstrated by the spatial frequency spectrum (inverse fast Fourier transform (IFFT)). The higher-order modes in CO<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>-written LPFGs and tilted LPFGs enhance the sensitivity to high-frequency ultrasound waves. This sensitivity arises from the broadband frequency resonance condition spanning 1 to 80 MHz in randomly spaced deformation-formed FP cavities. By analyzing the transmission and spatial frequency spectra of CO<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>-and UV-written LPFGs, where the latter fails to respond to ultrasound signals beyond 10MHz, we establish a framework for practical high-sensitivity ultrasound sensing.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".