Table of Contents
Fetching ...

Blind mitigation of foreground-induced biases on primordial $B$ modes for ground-based CMB experiments

Aliza Mustafa, Alessandro Carones, Nicoletta Krachmalnicoff, Marina Migliaccio, Carlo Baccigalupi

Abstract

Observations of the Cosmic Microwave Background (CMB) B-mode polarisation provide a unique probe of inflationary physics. Extracting a reliable constraint on the tensor-to-scalar ratio $r$ nonetheless demands stringent suppression of diffuse Galactic foregrounds, whose residuals can bias the inferred signal. This work introduces and evaluates two extensions of the Needlet Internal Linear Combination (NILC) framework aimed at reducing foreground-induced biases on $r$. The first extension implements the deprojection of selected foreground moments directly within the component-separation step. The second performs a likelihood-level marginalisation over residual foreground power using a data-driven template. Using Simons Observatory Small Aperture Telescope (SO-SAT) - like simulations, we show that both methods effectively control residual contamination, yielding unbiased estimates of $r$ and a consistent reconstruction of the lensing B-mode amplitude. These results indicate that enhanced foreground-mitigation strategies will be useful for next-generation CMB polarisation analyses seeking a robust detection of primordial B-modes.

Blind mitigation of foreground-induced biases on primordial $B$ modes for ground-based CMB experiments

Abstract

Observations of the Cosmic Microwave Background (CMB) B-mode polarisation provide a unique probe of inflationary physics. Extracting a reliable constraint on the tensor-to-scalar ratio nonetheless demands stringent suppression of diffuse Galactic foregrounds, whose residuals can bias the inferred signal. This work introduces and evaluates two extensions of the Needlet Internal Linear Combination (NILC) framework aimed at reducing foreground-induced biases on . The first extension implements the deprojection of selected foreground moments directly within the component-separation step. The second performs a likelihood-level marginalisation over residual foreground power using a data-driven template. Using Simons Observatory Small Aperture Telescope (SO-SAT) - like simulations, we show that both methods effectively control residual contamination, yielding unbiased estimates of and a consistent reconstruction of the lensing B-mode amplitude. These results indicate that enhanced foreground-mitigation strategies will be useful for next-generation CMB polarisation analyses seeking a robust detection of primordial B-modes.
Paper Structure (13 sections, 17 equations, 11 figures, 5 tables)

This paper contains 13 sections, 17 equations, 11 figures, 5 tables.

Figures (11)

  • Figure 1: SO-SAT forecasted hit-count map shown in equatorial coordinates.
  • Figure 2: Cosine needlet bands used for needlet filtering with peaks at $\ell_\mathrm{peaks} = [0, 100, 200]$.
  • Figure 3: $B$-mode angular power spectra of noise (dotted lines) and foreground residuals (solid lines) for NILC (violet) and cMILC (orange). All angular power spectra represent an average over 300 simulations. A uniform binning with $\Delta \ell=10$ is adopted. The average input CMB (with $r=0$) power spectrum obtained after applying the same masking to 300 simulated CMB-only maps, which contain lensing, is shown with the grey solid line. Results are reported for two foreground scenarios: d1s1 (left panel) and d10s5 (right panel), and assuming the baseline optimistic noise model. The grey shaded area indicates the amplitude range targeted by SO for the primordial tensor signal: $r \in [0.003, 0.028]$.
  • Figure 4: Averaged reconstructed CMB $B$-mode power spectra obtained from 300 simulations using the NILC (violet) and cMILC (orange) pipelines for the d1s1 (upper panel) and d10s5 (lower panel) foreground models. The solid grey line indicates the input CMB spectrum for $r = 0$. A uniform binning with $\Delta \ell=10$ is adopted. Colored markers represent the mean recovered bandpowers, with error bars showing the statistical dispersion across simulations. Data points have been debiased for reconstruction noise by subtracting the mean angular power spectrum of noise residuals obtained in each case.
  • Figure 5: $B$-mode maps of Galactic foregrounds, shown either as simulation inputs (first and third rows) or as reconstructed with GNILC (second and fourth rows), for the d1s1 foreground model at the six SO frequency channels. All maps are displayed in units of $\mu$K.
  • ...and 6 more figures