Real-Time Megapixel Electro-Optical Imaging of THz Beams with Probe Power Normalization
Bibliographic record
Abstract
In this work, we present a simple method to improve the spatial uniformity of two-dimensional electro-optical imaging of terahertz (THz) beams. In this system, near-field THz images are captured by fully illuminating a sample using conventional optical microscope objectives. Unfortunately, due to the linear relationship between the optical probe power and the measured THz electric field, any spatial variation in probe intensity translates directly into a variation of the recorded THz electric field. Using a single normalized background frame information map as a calibration tool prior to recording a sequence of THz images, we show a full recovery of a two-dimensional flat field for various combinations of magnification factors. Our results suggest that the implementation of dynamic intensity profile correction is a promising avenue for real-time electro-optical imaging of THz beams.
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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".