Transient waveform estimation of high-speed MCM networks using complex frequency hopping
Why this work is in the frame
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Bibliographic record
Abstract
The authors point out that moment-matching techniques that have been proposed for efficient transient waveform estimation of interconnect networks used in modeling MCMs can be inaccurate in high-speed systems by failing to detect some of the dominant high frequency network poles which lie far from the expansion point but near the imaginary axis in the frequency plane. Here, an approach for generating, with an accuracy check, all the dominant poles within the frequency range of interest using complex frequency hopping (CFH) is presented. The method, based on a binary search strategy, uses multiport complex moment-matching in the frequency s plane. CFH allows for the efficient analysis of large networks which include lossy, coupled transmission lines and nonlinear terminations, with estimated waveforms converging to simulation accuracy. Several examples which demonstrate the accuracy of the proposed technique are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.000 |
| 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) | 0.001 | 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 it