MapBasedR

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Summary

We checked the case in Victor's forecasts using our map-based code on PySM simulations. Bullet-point results (details below):

  • Assuming no delensing:
  • Assuming a 0.25 delensing factor:

Simulations

We used PySM to generate full-sky simulations including:

  • Power-law synchrotron (spatially-varying spectral index).
  • Single-component thermal dust (spatially-varying temperature and spectral index).
  • , partially de-lensed CMB.
  • Noise levels compatible with Victor's case.

The simulations are cut using a map defined by selecting the cleanest 4000 sq-deg of the sky in polarization.

Foreground removal

We run a map-based bayesian foreground-removal code on the simulations. The code samples the fully-resolved amplitudes of the three different components as well as spectral parameters ( and ). The latter are assumed constant on larger pixels, with HEALPix resolution (corresponding to ~4 deg). Fig. below shows the B-mode map at 145 MHz (left) and the mean CMB-only B-mode map output by the code.

Bmap.png Bmapfg.png

Estimating r

We compute the B-mode power spectrum for each simulation and fit a primordial + lensing template with amplitudes for both components (the first one being ). For this we only use multipoles . See result below for the no-delensing and 0.25-delensing cases. Clplot.png