A Sub-Nanosecond Time Interval Detection System Using FPGA Embedded I/O Resources
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 TDCs makes them sensitive to process and 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 on the fabric for low cost purposes. A Sub-Nanosecond Time Interval Detection System, able to overcome process and temperature (PT) variations, was designed and implemented in an FPGA. Unlike other FPGA-based TDCs, this new solution uses embedded PT invariant digital delay lines and deserializers included in I/O ports, along with a stable clock oscillator resulting in low logic usage. The proposed design consists of oversampling digital signals to enable the creation of absolute timestamps down to 75 ps resolution (31.85 ps <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RMS</sub> ). 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 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 | 0.001 |
| 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".