Dish surface characterization for HIRAX and CHORD using metrology and simulations
Bibliographic record
Abstract
Understanding the expansion history of the universe is crucial to modern cosmology, as it offers insights into the nature of dark energy and dark matter, as well as the formation and evolution of large-scale structures. The Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) and the Canadian Hydrogen Observatory and Radio-transient Detector (CHORD) are next-generation radio interferometers designed to measure baryonic acoustic oscillations (BAOs) through 21~cm intensity mapping (IM) and also act as a powerful platform for studying fast radio bursts (FRBs), pulsars and cross-correlation studies. Achieving precision cosmology with 21~cm IM techniques necessitates that HIRAX and CHORD interferometers meet stringent design, alignment, and calibration requirements. Thus, to develop redundant front-end electronic systems, feeds, and precise metrology methods, the Deep-Dish Development Array (D3A) was deployed at the Dominion Radio Astrophysical Observatory (DRAO). This small interferometric prototype array, comprising 2 three-meter and 3 six-meter composite dishes, serves as a testbed for various technologies, including antenna feed and mount design, reflector fabrication methods, the signal conditioning chain, and the readout system for HIRAX and CHORD. This thesis focuses on the dish surface characterization for CHORD and HIRAX, emphasizing the necessity of redundancy to achieve the desired scientific objectives. It discusses the mathematical framework required to analyze data from precise metrology techniques, such as laser tracker, photogrammetry, and finite element analysis. The implementation and results from these analyses are presented, highlighting the critical steps taken to ensure the accuracy and precision of the dish surface. Furthermore, the effects of these surface deformations on the telescope's beam pattern are investigated through electromagnetic (EM) simulations in CST Studio Suite, which helps determine the dish tolerances and optimal parameters needed to achieve redundancy targets. Finally, the concept of beam covariance is introduced as a metric to quantify the spatial variations within the beam patterns due to these surface deformations
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".