BEYONDPLANCK

VI. Noise characterization and modeling

¹ Institute of Theoretical Astrophysics, University of Oslo, Blindern, Oslo, Norway
e-mail: h.t.ihle@astro.uio.no
² Dipartimento di Fisica, Università degli Studi di Milano, Via Celoria 16, Milano, Italy
³ INAF-IASF Milano, Via E. Bassini 15, Milano, Italy
⁴ INFN, Sezione di Milano, Via Celoria 16, Milano, Italy
⁵ INAF – Osservatorio Astronomico di Trieste, Via G.B. Tiepolo 11, Trieste, Italy
⁶ Planetek Hellas, Leoforos Kifisias 44, Marousi, 151 25 Greece
⁷ Department of Astrophysical Sciences, Princeton University, Princeton, NJ, 08544 USA
⁸ Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, California, USA
⁹ Department of Physics, Gustaf Hällströmin katu 2, University of Helsinki, Helsinki, Finland
¹⁰ Helsinki Institute of Physics, Gustaf Hällströmin katu 2, University of Helsinki, Helsinki, Finland
¹¹ Computational Cosmology Center, Lawrence Berkeley National Laboratory, Berkeley, California, USA
¹² Haverford College Astronomy Department, 370 Lancaster Avenue, Haverford, Pennsylvania, USA
¹³ Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85741 Garching, Germany
¹⁴ Dipartimento di Fisica, Università degli Studi di Trieste, Via A. Valerio 2, Trieste, Italy

Received: 23 March 2022
Accepted: 17 June 2022

Abstract

We present a Bayesian method for estimating instrumental noise parameters and propagating noise uncertainties within the global BEYONDPLANCK Gibbs sampling framework, which we applied to Planck Low Frequency Instrument (LFI) time-ordered data. Following previous works in the literature, we initially adopted a 1/f model for the noise power spectral density (PSD), but we found the need for an additional lognormal component in the noise model in the 30 and 44 GHz bands. We implemented an optimal Wiener-filter (or constrained realization) gap-filling procedure to account for masked data. We then used this procedure to both estimate the gapless correlated noise in the time-domain, n_corr, and to sample the noise PSD parameters, ξⁿ = {σ₀, f_knee, α, A_p}. In contrast to previous Planck analyses, we assumed piecewise stationary noise only within each pointing period (PID), and not throughout the full mission, but we adopted the LFI Data Processing Center results as priors on α and f_knee. We generally found best-fit correlated noise parameters that are mostly consistent with previous results, with a few notable exceptions. However, a detailed inspection of the time-dependent results has revealed many important findings. First and foremost, we find strong evidence for statistically significant temporal variations in all noise PSD parameters, many of which are directly correlated with satellite housekeeping data. Second, while the simple 1/f model appears to be an excellent fit for the LFI 70 GHz channel, there is evidence for additional correlated noise that is not described by a 1/f model in the 30 and 44 GHz channels, including within the primary science frequency range of 0.1–1 Hz. In general, most 30 and 44 GHz channels exhibit deviations from 1/f at the 2–3σ level in each one-hour pointing period, motivating the addition of the lognormal noise component for these bands. For certain periods of time, we also find evidence of strong common mode noise fluctuations across the entire focal plane. Overall, we conclude that a simple 1/f profile is not adequate for obtaining a full characterization of the Planck LFI noise, even when fitted hour-by-hour, and a more general model is required. These findings have important implications for large-scale CMB polarization reconstruction with the Planck LFI data and the current work is a first attempt at understanding and mitigating these issues.