Enhanced Accuracy in On-Wafer Noise Figure Measurements at Sub-Terahertz Frequencies
Bibliographic record
Abstract
This paper delves into the precise on-wafer measurement of the noise figure (NF) of active circuits operating at millimetre-wave and sub-Terahertz frequencies. The focus lies on addressing the inherent challenge of the source impedance deviation at the input port plane of the die-under-test (DUT) from a matched load, a factor that significantly impacts the accuracy of NF measurements. The proposed testing system features an automated source tuner designed to counteract the non-idealities of ancillary components, including probes, cables, noise sources, switches, adapters, and frequency extenders, contributing to the impedance deviation. The testing system enables the measurement of the noise parameters of the DUT, allowing for the subsequent deduction of its noise figure. To validate its efficacy, the designed testing system is applied to measure the NF of a D-band distributed low-noise amplifier. The obtained results affirm the superior accuracy of the designed testing system when compared to the conventional Y-factor method.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".