Differential Confocal Fabry-Perot for the Optical Detection of Ultrasound
Bibliographic record
Abstract
The best detection limit of an optical system for the detection of ultrasound is obtained for a system limited by the shot noise. However, typical laser oscillators are not free of intensity and phase fluctuations, and such laser noise exceeds the shot‐noise level above a given laser light power. Moreover, since typical industrial surfaces are optically rough and absorbing, laser amplifiers are frequently used to increase the light power collected back from the surface. Such amplifiers add both intensity and phase fluctuations. While intensity fluctuations can be eliminated by a simple differential scheme when using a confocal Fabry‐Perot, no simple solution has been given to reduce the phase noise. In this paper, differential schemes that reduce both laser intensity and phase noises are proposed for the transmission and reflection configurations and experimental results on the noise reduction reached are presented. The advantages of this differential approach to image variable reflectivity surface parts and to relax detection laser requirements are then discussed.
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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 | 0.000 | 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)
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".