Redundant baseline calibration in CHIME : a first implementation & application as beam probe
Bibliographic record
Abstract
The nature of dark energy is one of the most intriguing scientific questions of the twenty-first century. There are many ways to probe dark energy, but one method involves detecting baryon acoustic oscillations (BAO) throughout the universe's history. BAO have a characteristic size scale and therefore act as a ``standard ruler,'' an advantageous property for a method of tracking the universe's expansion history. While baryon acoustic oscillations can be probed in many ways, one of the most intriguing and promising methods is through twenty-one centimeter hydrogen intensity mapping. Several experiments devoted to twenty-one centimeter hydrogen mapping will be coming on line in coming years, and these experiments have stringent calibration requirements due to the need to remove bright foreground signals. These calibration requirements necessitate new and improved methods for calibration. One proposed method is redundant baseline calibration, a self-calibration method which takes advantage of the massively redundant designs of many hydrogen intensity mapping experiments. With the Canadian Hydrogen Intensity Mapping Experiment as a test case, we demonstrate that the redundant baseline method is effective in even its simplest implementation for an idealized version of a real telescope. We then show that redundant baseline calibration fails in real CHIME Pathfinder data in a way that is consistent with deviations from redundancy observed in processed CHIME Pathfinder data. These deviations from redundancy are themselves consistent with the effects of feed-to-feed beam pattern variations, a possibility not considered in the conventional redundant baseline calibration algorithm. We simulate the CHIME Pathfinder including beam width perturbations and verify that similar failures in the redundant baseline calibration can be generated with beam perturbations. We then use the principles of redundant baseline calibration to solve for our simulated beam perturbations. Finally, we compare redundant baseline calibration results to point source holography results and show that the two are equivalent probes of relative feed-to-feed beam variation. We conclude that redundant baseline calibration is a promising path forward in calibrating hydrogen intensity mapping experiments, both as a conventional calibration method and as a probe of beam structure
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".