Ring core fiber supporting orbital angular momentum for modal multiplexing
Bibliographic record
Abstract
We design and characterize ring core fibers supporting orbital angular momentum modes; our fibers are produced in-house at Universit´e Laval. These fibers are tested in a transmission system test bed to demonstrate the wide range of exploitation strategies that are supported. When combining specialty fiber with integrated, silicon photonic multiplexers the costs are kept low, and multiplexed signals can be easily inserted into systems and technologies with tributaries for signal mode operation. We have demonstrated polarization maintaining operation on 12 data channels (6 modes) at 1.3 km that has the simplest digital signal processing. We used coherent detection of QPSK across the C-band, for a capacity of 40 Tb/s. When employing simple, commercially available 2-by-2 multiple-input, multiple-output processing the capacity can be increased to 65 Tb/s by suppressing polarization crosstalk. The performance of these fibers is best suited for short-distance links such as those in data centers. The ability to support a wide palate of modes gives flexibility; up to 12 simultaneous channels has already been demonstrated. Modes can be lit gradually as needed, or from initial deployment. The modes are polarization maintaining and very low crosstalk so that simple digital signal processing can be used. No multiple-input, multiple-output processing is required at distances under a kilometer. Our solutions are compatible with a migration from the current single-wavelength direct-detection approach to more aggressive, higher bandwidth systems. As data center technology moves to multiple wavelengths and/or coherent detection, the modal multiplexing with orbital angular momentum can provide the flexibility that is unattainable with scalar, linearly-polarized modal multiplexing.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".