Bibliographic record
Abstract
In this chapter, the quantum process of the Goos-Hänchen (GH) spatial shift is first derived out, then the coherence between spatial and angular shifts in the GH effect in the quantum state is discovered and a function of digital optical switch is developed. It is found that a waveguide corner structure always makes the reflected guide-mode have both the GH spatial and angular shifts when the incident beam is in the vicinity area of critical and Brewster angles. Meanwhile, these two GH shifts have the interesting coherent distributions with the incident angle, and only in the common linear response area the two GH shifts are mutual enhancing, then a mini refractive index modulation (RIM) of guided mode at the reflecting interface can create a great stable jump of reflected beam displacement at an eigenstate. As a result, on 220 nm silicon-on-insulator (SOI) waveguide platform, with a tapered multimode interference (MMI) waveguide a 5.0 × 10 18 cm − 3 concentration variation of free carriers can cause a digital total 8–25 μm displacement of the reflected beam on the MMI output end, leading to a 1 × N scale digital optical switching function. As a series of verifications, the numerical calculations, finite difference time domain (FDTD) simulations and experiments, are sustainable to the quantum GH shifts.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".