Monolithic Photonic Integrated Circuit Based on Silicon Nitride and Lithium Niobate on Insulator Hybrid Platform
Bibliographic record
Abstract
Lithium niobate on insulator (LNOI) has been demonstrated as a promising platform for photonic integrated circuits (PICs), thanks to its excellent properties such as strong electro‐optic effect, low material loss, and wide transparency window. Herein, a monolithic PIC for high‐speed data communication application on a lithium‐niobate‐etchless platform with silicon nitride (Si3N4) as a loading material is proposed and demonstrated. The fabricated PIC consists of four racetrack resonator modulators and a pair of four‐channel mode (de)multiplexers, which shows high data modulation rate of 70 Gbps for single channel and the total data throughput reaches up to 280 Gbps. To the best of knowledge, this is the first demonstration of PIC consisting of high‐speed electro‐optical modulators and (de)multiplexers with such high data capacity on Si3N4‐LNOI hybrid platform, which opens up new avenues for achieving large‐scale monolithic integration on LNOI platform in future.
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.
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".