A Reconfigurable Nanophotonic Architecture based on Phase Change Material
Bibliographic record
Abstract
Silicon photonics is an emerging technology allowing to take the advantage of high-speed light propagation to accelerate computing kernels in integrated systems. Micrometer-scale optical devices call for reconfigurable architectures to maximize resources utilization. Typical reconfigurable optical computing architectures involve micro-ring resonators for electro-optic modulation. However, such devices require voltage and thermal tuning to compensate for fabrication process variability and thermal sensitivity. This power-hungry calibration leads to significant static power overhead, thus limiting the scalability of optical architectures. In this paper, we propose to use non-volatile Phase Change Materials (PCM) elements to route optical signals only through the required resonators, hence saving calibration energy of bypassed resonators. The non-volatility of PCM elements allows maintaining the optical path. We investigate the efficiency of the PCM elements on the Reconfigurable Directed Logic (RDL) architecture. Results show that the static power is reduced by 32.8% on average and that 30% power saving is obtained from 158kHz reconfiguration frequency.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".