Coaxing Cosmic 21cm Fluctuations from the Polarized Sky using m-mode Analysis
Bibliographic record
Abstract
In this paper we continue to develop the m-mode formalism, a technique for efficient and optimal analysis of wide-field transit radio telescopes, targeted at 21 cm cosmology. We extend this formalism to give an accurate treatment of the polarised sky, fully accounting for the effects of polarisation leakage and cross-polarisation. We use the geometry of the measured set of visibilities to project down to pure temperature modes on the sky, serving as a significant compression, and an effective first filter of polarised contaminants. We use the m-mode formalism with the Karhunen-Loeve transform to give a highly efficient method for foreground cleaning, and demonstrate its success in cleaning realistic polarised skies observed with an instrument suffering from substantial off axis polarisation leakage. We develop an optimal quadratic estimator in the m-mode formalism, which can be efficiently calculated using a Monte-Carlo technique. This is used to assess the implications of foreground removal for power spectrum constraints where we find that our method can clean foregrounds well below the foreground wedge, rendering only scales $k_\parallel < 0.02 h \,\mathrm{Mpc}^{-1}$ inaccessible. As this approach assumes perfect knowledge of the telescope, we perform a conservative test of how essential this is by simulating and analysing datasets with deviations about our assumed telescope. Assuming no other techniques to mitigate bias are applied, we recover unbiased power spectra when the per-feed beam width to be measured to 0.1%, and amplifier gains to be known to 1% within each minute. Finally, as an example application, we extend our forecasts to a wideband 400-800 MHz cosmological observation and consider the implications for probing dark energy, finding a medium-sized cylinder telescope improves the DETF Figure of Merit by around 70% over Planck and Stage II experiments alone.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".