Noise analysis of fault tolerant active pixel sensors with and without defects
Bibliographic record
Abstract
As the sizes of imaging arrays become larger both in pixel count and area, the possibility of pixel defects increases during manufacturing and packaging, and over the lifetime of the sensor. To correct for these possible pixel defects, a Fault Tolerant Active Pixel Sensor (FTAPS) with redundancy at the pixel level has been designed and fabricated with only a small cost in area. The noise of the standard Active Pixel Sensor (APS) and FTAPS, under normal operating conditions as well as under the presence of optically stuck high and low faults, is analyzed and compared. The analysis shows that under typical illumination conditions the total noise of both the standard APS and FTAPS is dominated by the photocurrent shot noise. In the worst case (no illumination) the total mean squared noise of the FTAPS is only 15.5% larger than for the standard APS, while under typical illumination conditions the FTAPS noise increases by less than 0.1%. In the presence of half stuck faults the noise of the FTAPS compared to the standard APS stays the same as for the FTAPS without defects. However, simulation and experimental results have shown that the FTAPS sensitivity is greater than two times that of the standard APS leading to an increased SNR by more than twice for the FTAPS with no defects. Moreover, the SNR of a faulty standard APS is zero whereas the SNR of the FTAPS is reduced by less than half.
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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) | 0.001 | 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 | 0.000 |
| 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".