COMAP Early Science: IV. Power Spectrum Methodology and Results

TL;DR

This paper details the power spectrum methodology for COMAP's first season, introduces the FPXS estimator, addresses systematic errors, and provides the first direct constraint on the CO(1-0) power spectrum.

Contribution

It presents a robust power spectrum estimation method (FPXS) and applies it to first-season COMAP data, yielding the first direct constraint on the CO(1-0) clustering power spectrum.

Findings

Identified and removed a systematic error related to scanning strategy.

Demonstrated uncertainties scale with uncorrelated noise as expected.

Provided the first direct measurement of the CO(1-0) power spectrum.

Abstract

We present the power spectrum methodology used for the first-season COMAP analysis, and assess the quality of the current data set. The main results are derived through the Feed-feed Pseudo-Cross-Spectrum (FPXS) method, which is a robust estimator with respect to both noise modeling errors and experimental systematics. We use effective transfer functions to take into account the effects of instrumental beam smoothing and various filter operations applied during the low-level data processing. The power spectra estimated in this way have allowed us to identify a systematic error associated with one of our two scanning strategies, believed to be due to residual ground or atmospheric contamination. We omit these data from our analysis and no longer use this scanning technique for observations. We present the power spectra from our first season of observing and demonstrate that the uncertainties are integrating as expected for uncorrelated noise, with any residual systematics suppressed to a level below the noise. Using the FPXS method, and combining data on scales $k=0.051-0.62 \,\mathrm{Mpc}^{-1}$ we estimate $P_\mathrm{CO}(k) = -2.7 \pm 1.7 \times 10^4\mu\textrm{K}^2\mathrm{Mpc}^3$, the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum in the literature.