Unifying Figures of Merit: A Versatile Cost Function for Silicon Dangling Bond Logic
Why this work is in the frame
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Bibliographic record
Abstract
As Silicon Dangling Bond (SiDB) logic emerges as a promising beyond-CMOS technology, Figures of Merit (FoMs) to assess gate performance become crucial in implementing devices that are robust against environmental variations. Con-structing robust SiDB logic involves designing gates that excel across multiple FoMs. However, there exist no clear guidelines on the ideal ranges for FoM values, nor a systematic approach to designing SiDB gates that optimize across multiple FoMs. Motivated by this, this work focuses on addressing the following key objectives: 1) Introduction of a new FoM, called Band Bending Resilience. 2) Determination, presentation, and detailed discussion on the best achievable values for each FoM for all 2-input Boolean functions. 3) Presentation of the versatile cost function χ, unifying multiple FoM <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> tailored to specific application requirements and priorities. 4) Implementation of the optimization strategy using the cost function χ, which aims at designing SiDB logic with minimal cost, ensuring an optimal balance between all FoMs. Overall, this research contributes significantly to the understanding of SiDB logic, establishing a basis for future progress in the field.
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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) | 0.000 | 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 it