Bibliographic record
Abstract
In state-of-the-art laser ultrasonics (LU), the signal-to-noise ratio (SNR) is limited by the shot noise of the detected laser radiation. Further improving the SNR then requires averaging multiple signals or increasing generation and/or detection laser intensities. The former strategy is time consuming and the latter leads to surface damages. For signal-independent limiting noises, Hadamard multiplexing increases the SNR by averaging multiple signals in parallel using a single detector. Here we consider the use of Hadamard multiplexing in LU for the non-contact ultrasonic inspection of materials. By using 31 element Hadamard masks to modulate the spatial intensity distribution of the generation laser beam, the measured SNR is improved by a factor 2.8, in good agreement with the expected multiplexing or Fellgett advantage. In contrast to many other applications of Hadamard multiplexing, the SNR is improved for shot-noise-limited measurements since the shot noise level is independent of the signal in LU. The Hadamard multiplexing of the detection laser beam is also considered but can only lead to a throughput or Jacquinot advantage. However, for pulse-echo LU, the Hadamard multiplexing of both generation and detection laser beams allows using the synthetic aperture focusing technique (SAFT).
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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".