Progress in silicon platforms for integrated optics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Rapid progress has been made in recent years repurposing CMOS fabrication tools to build complex photonic circuits. As the field of silicon photonics becomes more mature, foundry processes will be an essential piece of the ecosystem for eliminating process risk and allowing the community to focus on adding value through clever design. Multi‐project wafer runs are a useful tool to promote further development by providing inexpensive, low‐risk prototyping opportunities to academic and commercial researchers. Compared to dedicated silicon manufacturing runs, multi‐project‐wafer runs offer cost reductions of 100× or more. Through OpSIS, we have begun to offer validated device libraries that allow designers to focus on building systems rather than modifying device geometries. The EDA tools that will enable rapid design of such complex systems are under intense development. Progress is also being made in developing practical optical and electronic packaging solutions for the photonic chips, in ways that eliminate or sharply reduce development costs for the user community. This paper will provide a review of the recent developments in silicon photonic foundry offerings with a focus on OpSIS, a multi‐project‐wafer foundry service offering a silicon photonics platform, including a variety of passive components as well as high‐speed modulators and photodetectors, through the Institute of Microelectronics in Singapore.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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