0.3–1.5-GHz LNA With Wideband Noise and Power Matching for Radio Astronomy
Bibliographic record
Abstract
This letter presents a low-noise amplifier (LNA) that was developed for a new radio telescope comprised of 512 parabolic dish antennas. The LNA closely interfaces to a custom-made antenna feed with an impedance co-designed to provide noise matching over a 5:1 bandwidth (BW). Additionally, a method of broadband noise and power matching that allows the input impedance to be controlled independent of the optimum signal-source impedance to achieve minimum noise is also discussed. When measured in a 50-$\Omega $system, the LNA exhibits a return loss (RL) of$>$8 dB between 0.32 and 1.5 GHz, S21 of 32 ± 1.2 dB, IP1dB−37 dBm, and IIP3−20 dBm. Noise parameter measurements show$T_{\text {min}} \approx 13 \pm $4 K and noise temperatures$T_{50\,\Omega } \approx 18 \pm $6 K between 0.5 and 1.4 GHz.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".