Map-making LFI

Noise Monte Carlo Simulation

Overview

Calculating and handling full pixel-to-pixel noise covariances in Planck maps if feasible only at low resolution. To support the analysis of high-resolution maps, a Monte Carlo set of noise maps were produced. These noise Monte Carlos were produced at two levels of the analysis: 1) LFI Monte Carlo (MC) as part of the LFI data processing, and 2) Full Focal Plane (FFP) Monte Carlo as part of the joint HFI/LFI data processing. This page describes the LFI noise MC. For the FFP MC, see HL-sims.

Inputs

The noise MC assumes a three-parameter noise model: white noise level ($\sigma$), slope, and knee frequency ($f_\mathrm{knee}$), so that the noise power spectrum is assumed to have the form $ P(f) = \frac{2\sigma^2}{f_\mathrm{sample}}\left(\frac{f}{f_\mathrm{knee}}\right)^\mathrm{slope} $. Here $f_\mathrm{sample}$ is the sampling frequency of the instrument. The noise parameters were determined separately for each radiometer