A <inline-formula> <tex-math notation="LaTeX">$3\times 60\;\text{Gb/s}$</tex-math> </inline-formula> Transmitter/Repeater Front-End With <inline-formula> <tex-math notation="LaTeX">$4.3\;{\rm V}_{\rm PP}$</tex-math> </inline-formula> Single-Ended Output Swing in a 28nm UTBB FD-SOI Technology
Bibliographic record
Abstract
A versatile three-lane transmitter/repeater array was designed and manufactured in a production 28nm ultra-thin body and BOX (UTBB) FD-SOI CMOS technology. Each lane in the array can operate at 60 Gb/s with adjustable output swing between 2.6 and 4.3 Vpp with a measured input sensitivity of 10 mVpp at 40 Gb/s, and requires at least 40mVpp input signal level to fully saturate the output driver for maximum swing operation at 60 Gb/s. Scaled, cascaded single-ended CMOS inverter transimpedance amplifiers with resistive and inductive feedback and interstage series inductive peaking were used to form the preamplifiers of each lane. These were optimized for maximum bandwidth and large gain, and drive the >4Vpp swing series-stacked cascoded CMOS inverter output stage. The single-ended CMOS-inverter topologies ensure that the total power consumption scales with the data rate and reduce the lane footprint to that of a ground-signal pad I/O. The measured lane-to-lane isolation is better than 40 dB up to 55 GHz, while the measured Tx-toRx dynamic range, defined as the ratio of the maximum output swing and corresponding minimum input voltage and sensitivity, is larger than 54 dB up to 40 Gb/s.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.442 | 0.325 |
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".