An 8‐bit digital‐to‐time converter with pre‐skewing and time interpolation
Bibliographic record
Abstract
Abstract This study presents an 8‐bit delay line digital‐to‐time converter (DTC) with pre‐skewing and digital time interpolation. Pre‐skewing that lowers the per‐stage‐delay of delay lines beyond that set by the chosen technology is investigated. A cascode tri‐state inverter is proposed to improve the isolation between the input and output of interpolation cells so as to improve the linearity of the time interpolator. Design considerations that critically affect the linearity of the DTC are examined in detail. The impact of the slope of the inputs of the time interpolator on the latency and linearity of the interpolator is analysed and the maximum slope of the input of interpolators yielding the minimum latency without sacrificing linearity, is obtained. The timing errors of DTC are investigated and the considerations of the layout of the DTC are examined. The DTC is designed in a TSMC 65 nm 1.0 V CMOS technology and analysed using Spectre with BSIM3V3 device models. Post‐layout simulation results show the DTC offers 3.6 ps resolution, 580 MS/s conversion rate, and consumes 383 μ W.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".