We describe the first-season CO Mapping Array Project (COMAP) analysis pipeline that converts raw detector readouts to calibrated sky maps. This pipeline implements four main steps: gain calibration, filtering, data selection, and mapmaking. Absolute gain calibration relies on a combination of instrumental and astrophysical sources, while relative gain calibration exploits real-time total-power variations. High-efficiency filtering is achieved through spectroscopic common-mode rejection within and across receivers, resulting in nearly uncorrelated white noise within single-frequency channels. Consequently, near-optimal but biased maps are produced by binning the filtered time stream into pixelized maps; the corresponding signal bias transfer function is estimated through simulations. Data selection is performed automatically through a series of goodness-of-fit statistics, including
We present the deconvolved distribution estimator (DDE), an extension of the voxel intensity distribution (VID), in the context of future observations proposed as part of the CO Mapping Array Project (COMAP). The DDE exploits the fact that the observed VID is a convolution of correlated signal intensity distributions and uncorrelated noise or interloper intensity distributions. By deconvolving the individual VID of two observables away from their joint VID in a Fourier-space operation, the DDE suppresses sensitivity to interloper emission while maintaining sensitivity to correlated components. The DDE thus improves upon the VID by reducing the relative influence of uncorrelated noise and interloper biases, which is useful in the context of COMAP observations that observe different rotational transitions of CO from the same comoving volume in different observing frequency bands. Fisher forecasts suggest that the theoretical sensitivity in the DDE allows significant improvements in constraining power compared to either the cross power spectrum or the individual VID data, and matches the constraining power of the combination of all other one- and two-point summary statistics. Future work should further investigate the covariance and model-dependent behaviour of this novel one-point cross-correlation statistic.
more » « less- NSF-PAR ID:
- 10398766
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 520
- Issue:
- 4
- ISSN:
- 0035-8711
- Format(s):
- Medium: X Size: p. 5305-5316
- Size(s):
- ["p. 5305-5316"]
- Sponsoring Org:
- National Science Foundation
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