Application of Two-Photon-Absorption Pulsed Laser for Single-Event-Effects Sensitivity Mapping Technology
Bibliographic record
Abstract
Single-event effects (SEEs) in integrated circuits and devices can be studied by utilizing ultra-fast pulsed laser system through Two Photon Absorption process. This paper presents technical ways to characterize key factors for laser based SEEs mapping testing system: output power from laser source, spot size focused by objective lens, opening window of Pockels cell, and calibration of injected laser energy. The laser based SEEs mapping testing system can work in a stable and controllable status by applying these methods. Furthermore, a sensitivity map of a Static Random Access Memory (SRAM) cell with a 65 nm technique node was created through the established laser system. The sensitivity map of the SRAM cell was compared to a map generated by a commercial simulation tool (TFIT), and the two matched well. In addition, experiments in this paper also provided energy distribution profile along Z axis that is the direction of the pulsed laser injection and threshold energy for different SRAM structures.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".