BeyondPlanck VI. Noise characterization and modelling

Abstract

We present a Bayesian method for estimating instrumental noise parameters and propagating noise uncertainties within the global BeyondPlanck Gibbs sampling framework, and apply this to Planck Low Frequency Instrument (LFI) time-ordered data. Following previous literature, we initially adopt a $1/f$ model for the noise power spectral density (PSD), but find the need for an additional lognormal component in the noise model for the 30 and 44\,GHz bands. We implement an optimal Wiener-filter (or constrained realization) gap-filling procedure to account for masked data. We then use this procedure to both estimate the gapless correlated noise in the time-domain, $n_{\mathrm{corr}}$, and to sample the noise PSD parameters, ${\xi }^n=\{{\sigma }_0,f_{\mathrm{knee}},\alpha ,A_{\mathrm{p}}\}$. In contrast to previous \textit{Planck} analyses, we assume piecewise stationary noise only within each pointing period (PID), not throughout the full mission, but we adopt the LFI Data Processing Center (DPC) results as priors on $\alpha$ and $f_{\mathrm{knee}}$. On average, we find 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 reveals 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 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. (Abridged)

26 pages, 29 figures, as accepted in A&A

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• BeyondPlanck XIII. Intensity foreground sampling, degeneracies, and priors
• BeyondPlanck VII. Bayesian estimation of gain and absolute calibration for CMB experiments
• BeyondPlanck XII. Cosmological parameter constraints with end-to-end error propagation
• Cosmoglobe DR1 results. I. Improved Wilkinson Microwave Anisotropy Probe maps through Bayesian end-to-end analysis
• BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation
• From BeyondPlanck to Cosmoglobe: Preliminary $WMAP$ $Q$-band analysis
• BeyondPlanck XVI. Limits on Large-Scale Polarized Anomalous Microwave Emission from Planck LFI and WMAP
• BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation
• BeyondPlanck IV. On end-to-end simulations in CMB analysis -- Bayesian versus frequentist statistics
• BeyondPlanck II. CMB map-making through Gibbs sampling
• BeyondPlanck V. Minimal ADC Corrections for Planck LFI
• Optimal bolometer transfer function deconvolution for CMB experiments through maximum likelihood mapmaking
• On the computational feasibility of Bayesian end-to-end analysis of LiteBIRD simulations within Cosmoglobe