A broadband Variable Gain Amplifier for the Square Kilometer Array
Bibliographic record
Abstract
In this paper, an inductorless broadband linear-in-dB Variable-Gain Amplifier (VGA) circuit for use in the Square Kilometer Array (SKA) is presented. A two-transistor topology, which realizes a linear-in-dB function, is used to design a differential VGA. The VGA is both input and output power matched to 100Ω differential sources and loads. The design is fabricated in ST 65nm CMOS technology with a 1V power supply. Measurement results show that the VGA has a 25dB variable gain range, input P1dB of -25dBm to -32dBm with control voltage ranging from 0.5V to 1.0V, and is designed to work in a frequency range from 0.7GHz to 1.4GHz, which is the frequency range of the mid-band SKA receiver. The total power consumption of the VGA is 1mW with another 6mW consumed by an input-match circuit and 1mW consumed by an output buffer circuit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".