cmbscat

Map-based emulator for CMB systematics with scattering covariances

cmbscat is a pip installable package that can synthesize new full-sky map samples (emulations) on the HEALPix sphere which are both visually and statistically similar to the ones found in an (eventually small) dataset of simulations.

cmbscat relies heavily on the HealpixML library for efficient scattering covariance computation on the HEALPix sphere.

Install with pip

You can install it simply doing:

pip install cmbscat

Usage

You can then set generate a new dataset of CMB systematics maps by doing:

from cmbscat import cmbscat_pipe

# Set emulator parameters
params = {
    'NNN'          : 10,             # Number of input reference maps
    'gauss_real'   : True,             # Generate new input data as Gaussian realizations from pixel covariance of original data
    'NGEN'         : 10,               # Batch size for gradient descent
    'n_samples'    : 10,               # Samples in the input dataset
    'nside'        : 16,               # N_side of input maps
    'NORIENT'      : 4,                # Orientations in the SC
    'nstep'        : 50,              # Steps in gradient descent
    'KERNELSZ'     : 3,                # Wavelet kernel size
    'outname'      : 'example',        # Output name
    'outpath'      : './data/',        # Output path
    'data'         : 'variable_gain_sims.npy'  # Input data path
}

# Initialize pipeline...
pipeline = cmbscat_pipe(params)

#...and run! This generates NGEN new maps for each of the n_samples input maps
pipeline.run()

Tutorial Notebook

You can find an introductory notebook explaining all features of the cmbscat package here.

Specifically we apply it to simulated maps of an example of CMB satellites instrumental systematics, as described in [Campeti et al. 2025].

Citations

Should this code be used in any way, we kindly ask that the following article is cited:

@article{campeti:systematics_emulator, 
   author      = "Paolo Campeti, Jean-Marc Delouis, Luca Pagano, Erwan Allys, Massimiliano Lattanzi, Martina Gerbino",
   title       = "From few to many maps: A fast map-level emulator for extreme augmentation of CMB systematics datasets",
   eprint = "",
   archivePrefix = "arXiv",
   primaryClass = "astro-ph.CO",
   month = "",
   year = "2025"
}