Towards a universal RF photonic integrated circuit architecture for microwave applications
Bibliographic record
Abstract
There has been a plethora of publications over the last decade that have described essentially the same Generalized Mach-Zehnder Interferometer (GMZI) circuit architecture: a 1 × N splitter directly interconnected to a N × 1 combiner via an array of N electro-optic LiNbO3-based phase modulators, each circuit adapted to particular design goals. This paper introduces a novel extension of the circuit architecture that subsumes all these MZI circuits in the prior art by replacing the N × 1 combiner of a GMZI-based architecture by an N × N optical Discrete Fourier Transform (DFT) network to generate a frequency comb with regularly spaced harmonics of frequency qωRFwhere ωRFis the frequency of the RF drive signal applied to the phase modulators. All harmonic orders equivalent modulo N to the output port number p exit that port. As the circuit generates N spatially separated phase correlated subcarriers, it can be used to provide multi-carriers for transmission formats such as orthogonal frequency division multiplexing (OFDM) that will enable the satisfaction of the terabit data ratedemands anticipated in the near future. The proposed circuit can be implemented practically in any material platform that offers linear electro-optic phase modulators.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".