Gain-Enhanced Distributed Amplifier Using Negative Capacitance
Bibliographic record
Abstract
This paper presents a new high-gain structure for the distributed amplifier. Negative capacitance cells are exploited to ameliorate the loading effects of parasitic capacitors of gain cells in order to improve the gain of the distributed amplifier while keeping the desired bandwidth. In addition, the negative capacitance circuit creates a negative resistance that can be used to increase the amplifier bandwidth. Implemented in 0.13-μm IBM's CMRF8SF CMOS, the proposed six-stage distributed amplifier presents an average gain of 13.2 dB over a bandwidth of 29.4 GHz. The measured input return loss is less than -9 dB and the output return loss is less than -9.5 dB over the entire bandwidth. With a chip area of 1.5 mm × 0.8 mm, the amplifier consumes 136 mW from a 1.5-V dc power supply.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".