Manipulation of the coherent spatial and angular shifts of Goos-Hänchen effect to realize the digital optical switch in silicon-on-insulator waveguide corner
Bibliographic record
Abstract
In this work, based on the quantum process of the Goos-Hänchen (GH) spatial shift, a quantum process of the GH angular shift is also theoretically investigated. Then, the coherence between spatial and angular shifts in the GH effect is discovered and developed to manipulate the final total displacement for a digital optical switch. It is found that a waveguide corner structure always makes the reflected guide-mode have a GH angular shift in the minus direction when the incident beam is in the Brewster angle vicinity, while it always makes the spatial shift in the plus direction. Meanwhile, the coherence of these two GH shifts has an interesting distribution with the incident angle, and only in the common linear response area to the incident angle, the two GH shifts are mutually enhancing, and then a mini refractive index modulation of the guided-mode at the reflecting interface can create a great stable jump of reflected beam displacement at an eigenstate under the GH effect. As a result, on the 220 nm CMOS-compatible silicon-on-insulator waveguide platform, with a tapered multimode interference (MMI) waveguide, a 5 × 1018cm−3 concentration variation of free carriers can create an absolute digital total displacement of 8–25 μm of the reflected beam on the MMI waveguide output end, leading to a 1 × 5 scale digital optical switching function.
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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".