Piecewise quadratic waveform matching with successive chord iteration
Bibliographic record
Abstract
While fast timing analysis methods based on model order re-duction have been well established for linear circuits, the tim-ing analysis for non-linear circuits, which are dominant in dig-ital circuits, is usually performed by a SPICE-like, numerical integration-based approach solving differential equations. In this paper, we propose a new technique that leads to the transient so-lution of charge / discharge paths with a complexity equivalent to only K DC operating point calculations, where K is the number of transistors along the path. This is accomplished by approx-imating each nodal voltage as a piecewise quadratic waveform, whose characteristics can be determined by matching the charge / discharge currents calculated by the capacitive components and the resistive components. Successive chord method is then ap-plied to reduce the matrix construction and inversion overhead. Experiments on a wide range of circuits show that an average of 20 times speed-up over HSPICE simulation (transient time only) with 10 picosecond step size can be achieved, while maintaining an average accuracy of 98.03%. I.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".