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Record W4376607974 · doi:10.1109/lmwt.2023.3272211

0.3–1.5-GHz LNA With Wideband Noise and Power Matching for Radio Astronomy

2023· article· en· W4376607974 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Microwave and Wireless Technology Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsMcGill UniversityUniversity of TorontoUniversity of Calgary
FundersUniversity of Calgary
KeywordsNoise (video)WidebandNotationElectrical engineeringAlgorithmMathematicsPhysicsComputer scienceEngineeringArithmeticArtificial intelligence

Abstract

fetched live from OpenAlex

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- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> system, the LNA exhibits a return loss (RL) of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;$ </tex-math></inline-formula> 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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{\text {min}} \approx 13 \pm $ </tex-math></inline-formula> 4 K and noise temperatures <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{50\,\Omega } \approx 18 \pm $ </tex-math></inline-formula> 6 K between 0.5 and 1.4 GHz.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.188
Teacher spread0.182 · 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