SEMSIM: Adaptive Multiscale Simulation For Single-Electron Devices
Why this work is in the frame
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Bibliographic record
Abstract
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Single-electron devices have drawn much attention in the last two decades. They have been widely used for device research and also show promise as a potential alternative to CMOS circuits due to their ultralow power dissipation. Three techniques have been used for single-electron device modeling in the past, including Monte Carlo (MC), master equation, and SPICE modeling. Among these, MC method provides accuracy, but lacks the time efficiency required for large-scale simulation. In this paper, we introduce an adaptive multiscale approach to single-electron device simulation using MC method as basis, which significantly improves time efficiency while maintaining accuracy. We have shown that it is possible to reduce simulation time up to nearly 40 times and maintain an average error of 3.3%. Going beyond simplistic approximations, we have modeled important secondary effects including cotunneling and Cooper pair tunneling, which are critical for device research. </para>
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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