Compact and fast response ultrasonic detection device based on two-wave mixing in a gallium arsenide photorefractive crystal
Bibliographic record
Abstract
An improved phase demodulator for the detection of ultrasound based on two-wave mixing (TWM) in the diffusion regime in a semi-insulating photorefractive GaAs crystal is presented. A new optical layout is proposed in which the total laser power is injected into the crystal to reduce the grating buildup time. The device is then less sensitive to ambient vibrations or motion of the inspected part. Another new feature of the device is a balanced receiver based on large area InGaAs detectors. The measured rejection ratio of this balanced receiver is 50 dB. However, in this new optical configuration the signal and pump beam paths cannot be made equal which results in some sensitivity to high frequency laser phase noise. The performance of the device operated with a cw and a pulsed laser source is described. A comparison with the conventional confocal Fabry–Perot in the transmission mode is also presented. As expected, the GaAs-based TWM photorefractive system is less sensitive than the Fabry–Perot at high frequencies but becomes more sensitive below some frequency value. For the 30 W pumping level used into the crystal and a 1 m long Fabry–Perot with 85% reflectivity mirrors, this value was found to be about 1.5 MHz. This feature is known to be useful in the cases where low frequencies have to be detected, higher frequencies being attenuated by the material. This is the case of coarse microstructure materials or viscous or mushy materials. This photorefractive configuration is also attractive like all photorefractive systems for compactness and the absence of any need for active stabilization. To obtain a sensitivity equal or better than that of the confocal Fabry–Perot in the transmission mode, this new setup can be used with an InP:Fe or a CdTe:V photorefractive crystal under an applied field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".