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A 4–12 GHz Hybrid LNA with Cryogenic Operation for Radio-Astronomy Receivers

2025· article· W7127431327 on OpenAlexaffabout
Deisy Formiga Mamedes, Nianhua Jiang, Dominic Garcia, A. Densmore

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsNoise figureLow-noise amplifierAmplifierBroadbandNoise temperatureTransistorY-factorNoise (video)Power consumption

Abstract

fetched live from OpenAlex

This paper presents the design of a broadband hybrid low-noise amplifier (LNA) utilizing 100-nm indium phosphide transistor technology developed by the National Research Council Canada for cryogenic operation in the 4–12 GHz frequency range. The amplifier is composed of four stages, each employing a common-source transistor configuration. In the specified frequency band, the LNA achieves a gain of 30.2 ± 1.4 dB and an average noise figure of 2.4 dB, with a minimum noise figure of 2.1 dB at room temperature. When cooled down to 15 K, the LNA demonstrates a gain of 32.6 ± 1.6 dB and an average noise temperature of 11.5 K, with a minimum noise of 7.3 K. The DC power consumption is 15.5 mW at cryogenic temperature.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.009
GPT teacher head0.209
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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