Extremely low noise UHF-band amplifiers for square kilometer array
Bibliographic record
Abstract
This paper demonstrates two designs of extremely low noise amplifiers in the low frequency range of 350 MHz to 1070 MHz. Hybrid microwave integrated circuit is adapted for a low noise design at this low frequency range. Discrete passive components with high-Q and large values are selected to integrate with the best low noise transistors to optimize the LNA performance. The first UHF band cryogenic LNA was designed with InP HEMTs in all three stages for Square Kilometer Array - mid telescope band-1 receiver. This LNA extended the low end frequency to 350 MHz, and achieved averaging 1.4 Kelvin of a record low noise temperature, more than 47 dB gain, and good input and output return losses < -10 dB over the broad bandwidth from 350 to 1050 MHz at 15 K. The second UHF band cryogenic LNA was developed for MeerKAT Array, a precursor of Square Kilometer Array. This LNA was designed with InP HEMT transistor at first stage to achieve best low noise performance and GaAs HEMTs for second and third stages to replace InP HEMTs and realize high gain and good amplitude stability at cryogenic temperature. The second LNA achieved a record low noise temperature of averaging 0.6 Kelvin, more than 45 dB gain, and good input and output return losses ≤ -12 dB over the wide bandwidth from 580 to 1070 MHz at 15 K.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".