SMICA propagation code

SMICA-weights-propagation

This script allows to combine a set of Planck frequency maps into a single component separated like map using SMICA weights. It has been used by the Planck team to propagate CMB and noise Monte Carlo realizations to get the set of SMICA simulations.

Dependancies

The script is written in Python2 and depends on several Python modules:

• healpy >= 1.7.4 (https://healpy.readthedocs.io/en/latest/)
• pyfits >= 3.4 (https://pythonhosted.org/pyfits/)
• numpy

Ancillary data

Ancillary data provided with the script correspond to:

• `transition_mask.fits.gz`: definition of the Xhigh area (see Planck Collaboration IV. 2018 for a description of the SMICA pipeline)
• `weights_T_smica_R3.00_<X>.txt` with X in `["Xhigh", "Xfull"]`: harmonic weights to be used in temperature.
• `weights_EB_smica_R3.00.txt`: harmonic weights to be used in polarization.

Input data

Input data consist in a set of 9 Planck frequency maps, having the same properties than the Planck simulation maps:

• Units: maps should be in `K_CMB` units, except for the 545GHz and 857GHz maps which should be in `MJy/sr` (conversion factors are explicitly given in the code).

• Beam convolution: the weights include a beam correction necessary to put all the maps at the same resolution. The beam window functions that we used are provided within the PLA, and can be used to generate new simulations.

• Calibration: As LFI beam window functions have been de-normalized to account for calibration correction of real data, our weights also include a 're-normalization' of LFI beam window function. Therefore, this can be ignored by users when generating new simulations.

The script provides a basic routine (named `my_freq_map_finder` L45) to retrieve input files from a given directory, which should be customized by users to their needs.

Examples

smica_coadd input_directory output_directory 0 1000
smica_coadd input_directory output_directory 0 1000 --polar

will process sequencially the realizations number #0 to #1000 from the input directory. One can call the script in a parallel mode, where realization indices are splitted over processes or threads.

Output data

The outputs of a temperature run are FITS files of one column corresponding to intensity pixel values. The outputs of a polarizatoin run are FITS files of two columns for Q and U stokes parameters. Units of the output maps are given in the UNITS header keyword.