COMAP Early Science. III. CO Data Processing

Abstract

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 χ 2 and multiscale correlation tests. Applying this pipeline to the first-season COMAP data, we produce a data set with very low levels of correlated noise. We find that one of our two scanning strategies (the Lissajous type) is sensitive to residual instrumental systematics. As a result, we no longer use this type of scan and exclude data taken this way from our Season 1 power spectrum estimates. We perform a careful analysis of our data processing and observing efficiencies and take account of planned improvements to estimate our future performance. Power spectrum results derived from the first-season COMAP maps are presented and discussed in companion papers.

COMAP Early Science. IV. Power Spectrum Methodology and Results

“…As described in Foss et al (2022), after the COMAP timeordered data have been filtered and calibrated, and the bad observations have been removed, the cleaned data set is compressed into a set of 3D maps. We make separate maps for the Lissajous scans and the CES scans, since these tend to have different systematics and statistical properties.…”

“…We estimate separate cross-spectra for the Lissajous and CES data, for each of the three CO fields that we have observed (Foss et al 2022). Since we found clear excess power in the Lissajous spectra, we do not include them in the main results, and we will here focus on the CES data.…”

“…This is due to the various filters applied to the time-ordered data to remove correlated noise and systematics, in addition to the effects of the scanning strategy. For more details, see Foss et al (2022). In order to get the best result, we need to take this into account when we calculate the spherically averaged power spectrum.…”

“…The low-level COMAP data-processing pipeline is summarized by Foss et al (2022). This pipeline converts raw uncalibrated observations into 3D maps, using redshifted CO line emission from distant galaxies as a tracer of the cosmic density field.…”

“…As described by Lamb et al (2022) and Foss et al (2022), the COMAP focal plane consists of 19 different feed horns, arranged in a hexagonal pattern, with about 12′ sky separation between the closest feeds. The signal entering each feed horn is sent through its own signal chain, with its own amplifiers and digital high-resolution spectrometers.…”