Low-Cost, Low-Loss, Ultra-Wideband Compact Feed for Interferometric Radio Telescopes
Bibliographic record
Abstract
We have developed, manufactured, and tested a new feed design for interferometric radio telescopes with “large-N, small-D” designs. Such arrays require low-cost and low-complexity feeds for mass production on reasonable timescales and budgets, and also require those feeds to be compact to minimize obstruction of the dishes, along with having ultra-wide frequency bands of operation for most current and future science goals. The feed presented in this paper modifies the exponentially tapered slot antenna (Vivaldi) and quad-ridged flared horn antenna designs by having an oversized backshort, a novel method of maintaining a small size that is well-suited for deeper dishes ([Formula: see text]). It is made of laser cut aluminum and printed circuit boards, such that it is inexpensive ([Formula: see text][Formula: see text]USD per feed in large-scale production) and quick to build; it has a 5:1 frequency ratio, and its size is approximately a third of its longest operating wavelength. We present the science and engineering constraints that went into design decisions, the development and optimization process, and the simulated performance. A version of this feed design was optimized and fabricated for the Canadian Hydrogen Observatory and Radio-transient Detector (CHORD) prototypes. When simulated on CHORD’s very deep dishes ([Formula: see text]) and with CHORD’s custom first-stage amplifiers, the on-sky system temperature [Formula: see text] of the complete receiving system from dish to digitizer remains below 30[Formula: see text]K over most of the 0.3–1.5[Formula: see text]GHz band, and maintains an aperture efficiency [Formula: see text] between 0.4 and 0.6. The entire receiving chain operates at ambient temperature. The feed is designed to slightly under-illuminate the CHORD dishes, in order to minimize coupling between array elements and spillover.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".