NRC-HAA Cryogenic Radio Receiver Development
Bibliographic record
Abstract
The Radio Instrumentation Team (RIT) team at NRC Herzberg in Victoria, Canada, is developing a dual linear polarization, cryogenic radio astronomy receiver covering the frequency range of 30.5 to 50.5 GHz for the next generation Very Large Array (ngVLA) project. The specification of this receiver development is aligned with ngVLA Band 5 requirements. This receiver is designed for a noise temperature of less than 25 K over the bandwidth. The proposed receiver uses a vacuum vessel and a two-stage cryopump system for a cryogenic environment which provides 16 K and 70 K stages. The proposed receiver consists of a cryostat with a cooled feed horn, a turnstile OMT plus two integrated noise couplers for noise calibration, two mHEMT MMIC cryogenic low noise amplifiers with noise temperature lower than 14 K, IR filters, and a vacuum window to create a low-loss transmission of electromagnetic fields into the cryostat. The RIT team is also working on designing and developing various high-efficiency and wideband feed horns, vacuum windows, and OMTs. So far, a compact, low noise octave band OMT, multiple octave band feed horns, and a vacuum window covering the frequency range of 25-50 GHz have been designed. Most of the waveguide components designed and developed for the ngVLA Band 5 and octave band receiver are scalable to higher and lower frequency bands.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.013 |
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".