Silicon Photonic Switch Subsystem With 900 Monolithically Integrated Calibration Photodiodes and 64-Fiber Package
Bibliographic record
Abstract
A packaged and fully operational 32 × 32 silicon photonic switch chip having 448 switch cells and 1856 crossings is demonstrated. The switch chip includes 900 monolithically integrated photodiodes used for calibrating the thermo-optic Mach-Zehnder switch cells. The calibration procedure employs an external laser source and follows a reachability-tree sequence to calibrate all switch cells. The accuracy of the calibration is demonstrated by the measurement of switch cell extinction ratios, for both states of each switch cell. The mean extinction ratio for both states is 35 dB. Arbitrary light path switching is demonstrated. Measurement of the channel-to-channel crosstalk was performed for a large number of aggressor and victim light path combinations. The matrix crosstalk is dominated by contributions from waveguide crossings. The die was wire-bonded to a custom ceramic package, to which a 68-fiber ribbon was permanently attached, which coupled the input and output optical signals to edge couplers on the chip through a waveguide pitch- and mode-concentrating silica chip. The fiber-to-fiber loss of on-chip loopback waveguides was less than 6.5 dB from 1530 to 1565 nm. The entirety of switch cells and monitors was driven by controller boards and A/D chips using a controller field-programmable gate array (FPGA). The calibration procedure was completed in less than 10 min using only the on-chip monitors, without off-chip detectors. The chip was recalibrated after six months storage, and the measured change in drive current was within the calibration uncertainty, indicating that the chip and driver are stable over time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".