Phase change reconfigurable grating couplers with ultrahigh modulation contrast
Bibliographic record
Abstract
Silicon photonics has matured over the last decade as a unique platform for highly miniaturized photonic integrated systems seamlessly integrated with electronics allowing the realization and commercialization of highly compact devices with ultrafast data transfer rates and significantly reduced power consumption. Although such submicron scale photonic and waveguide structures enable dense on-chip device integration, they also result in reduced efficiency in fiber-to-waveguide coupling mainly due to increased mode area mismatch. As a result, one of the key challenges faced in current technology platforms has been to efficiently couple light without additional fabrication, post-processing, and complex optical alignment. In-plane grating couplers (GC) have been a widely preferred coupling platform, mainly because of low fabrication costs, ease of alignment and high-level of flexibility in circuit design. A wide range of coupling platform designs have been investigated in the last decade including both passive and active designs. In passive design the coupling efficiency (CE) is fixed once the device is fabricated, however in active designs various tuning mechanism have been explored to modulate the CE, but at the expense of increased power consumption and reduced CE. Using inverse design techniques, we demonstrate CMOS compatible, reconfigurable phase change chalcogenide-on-insulator based apodised GC having maximized CE of more than 50% at λ=1550nm when the phase of the chalcogenide is in amorphous state. When the phase is switched to crystalline state, a near zero CE is shown allowing the design to be both non-volatile and reversibly reconfigurable with highest transmission modulation contrast of more than 50db.
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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 | 0.000 | 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".