Linear cross talk in wave-mixing optical cross connects
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
Multistage cross connects with wave-mixing conversion have two essential characteristics. First, individual converters are simultaneously shared by a significant number of channels. Second, individual channels may be converted through one or more cascaded wave-mixing conversions. The combination of both design principles contributes to the degradation of the transmission performance in the networks, to the point where it may be legitimate to question the practicality of multistage wave-mixing networks. To discuss the matter, a cross-talk analysis is conducted for wave-mixing networks with feed-forward multistage structures, and 2×2 switching elements, such as multilog networks. It is found that the dominant form of cross talk is of the first-order intraband type and that such cross talk accumulates in switching elements and in wave-mixing converters. Such induced cross talk not only results in stringent component requirements both for switching elements and for demultiplexers integrated with wave-mixing converters. It also limits the scalability and cascadability of the nodes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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