A Sub-Nanosecond Edge Detection System using embedded FPGA fabrics
Bibliographic record
Abstract
The time to digital converter (TDC) concept is quite useful to obtain crucial timing information for nuclear radiation detection such as PET imaging applications. The high resolution nature of TDC makes them sensitive to processing and to temperature variations. Thus, a calibration procedure must often be performed to improve measurements. Moreover, field programmable gate array (FPGA)-based TDC exacerbates this problem because the transistor topology is fixed in the fabric for low cost purpose. A sub-nanosecond edge detection system able to overcome process, power supply voltage and temperature (PVT) variations was designed and implemented in an FPGA. Unlike other FPGA-based TDCs, this new solution uses embedded PVT invariant digital delay lines and deserializers included in I/O ports along with a stable clock oscillator resulting in low logic usage. The proposed approach consists in oversampling digital signals to enable absolute timestamps down to 75 ps resolution (31.85 ps rms). As a proof of concept, this paper reports timing resolution down to 321.5 ps.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".