Mitigating the effect of 1/f noise on the detection of the HI intensity mapping power spectrum from single-dish measurements

TL;DR

This paper evaluates methods to mitigate 1/f noise in HI intensity mapping with MeerKAT, demonstrating that advanced cleaning techniques and noise-aware map-making can significantly improve power spectrum recovery.

Contribution

The study introduces and compares multiple strategies, including SVD and noise covariance weighting, to effectively reduce 1/f noise impact in HI intensity mapping surveys.

Findings

SVD cleaning removes 40% of HI power at certain scales due to over-cleaning.

Including noise covariance in map-making reduces 1/f noise excess by up to 30%.

Pilot data shows 1/f noise is 10-20 times higher than white noise at relevant scales.

Abstract

We present and compare several methods to mitigate time-correlated (1/f) noise within the HI intensity mapping component of the MeerKAT Large Area Synoptic Survey (MeerKLASS). By simulating scan strategies, the HI signal, foreground emissions, white and correlated noise, we assess the ability of various data processing pipelines to recover the power spectrum of HI brightness temperature fluctuations. We use MeerKAT pilot data to assess the level of 1/f noise expected for the MeerKLASS survey and use these measurements to create realistic levels of time-correlated noise for our simulations. We find the time-correlated noise component within the pilot data to be between 10 and 20 times higher than the white noise level at the scale of k = 0.04 Mpc^-1. Having determined that the MeerKAT 1/f noise is partially correlated across all the frequency channels, we employ Singular Value Decomposition (SVD) as a technique to remove both the 1/f noise and Galactic foregrounds but find that over-cleaning results in the removal of HI power at large (angular and radial) scales; a power loss of 40 per cent is seen for a 3-mode SVD clean at the scale of k = 0.04 Mpc^-1. We compare the impact of map-making using weighting by the full noise covariance (i.e. including a 1/f component), as opposed to just a simple unweighted binning, finding that including the time-correlated noise information reduces the excess power added by 1/f noise by up to 30 per cent.