Bibliographic record
Abstract
With recent increasing demands for higher capacity in optical networks, there is a need for high-speed optical modulation. This desire is especially pronounced with the growth of high volume data centers. There is a demand for low-power modulators that can be placed on printed circuit boards. Mach-Zehnder modulators (MZM)s, in a range of different materials, are widely used for this purpose. However, their power consumption is determined by the relatively large electrode size which they require. Some time ago researchers in optical fiber switches introduced the concept of the loop-mirror for nonlinear applications. This device is conceptually an MZM in which two outputs are connected to make a loop at the end. Although loop-mirror was introduced in nonlinear optical switching it also can be used as an optical modulator.In this thesis, we introduce for the first time an integrated loop-mirror modulator (LMM). We show that this device requires one-half the switching voltage and one-quarter the power consumption of a conventional MZM. This device is implemented in silicon-on-insulator technology with carrier depletion junctions. The reverse-biased PN junction modulator is fabricated with two different electrode configurations (series push-pull and dual-drive). On-Off Keying (OOK) modulation at 20 Gb/s and Differential phase shift keying (DPSK) modulation at 10 Gb/s is demonstrated experimentally. The frequency response of the LMM is analyzed and we conclude that the power efficiency gains of the LMM are only present in the lumped electrode regime. In the traveling-wave (TW) electrode regime it is not possible to simultaneously velocity match the forward and backward going optical and electrical waves in the electrodes. As a reflective modulator the proposed LMM could find applications in passive optical networks (PON).
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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".