cosmoglobe,github

cosmoglobe is a python package that interfaces the Cosmoglobe Sky Model with Commander outputs for the purpose of producing astrophysical sky maps.

Features

See the documentation for a more comprehensive guide.

Initialize the Cosmoglobe Sky Model (this downloads and caches a ~800 MB file with the sky model data)

import cosmoglobe

model = cosmoglobe.sky_model(nside=256)

Simulate the sky at 150 GHz in units of MJy/sr, smoothed to 40 arcmin with a gaussian beam:

import astropy.units as u

emission = model(150*u.GHz, fwhm=40*u.arcmin, output_unit="MJy/sr")

Integrate over a bandpass:

import numpy as np
import healpy as hp
import matplotlib.pyplot as plt

# Reading in WMAP K-band bandpass profile.
bandpass_frequencies, bandpass_weights = np.loadtxt(wmap_bandpass.txt, unpack=True)

# The units of the detector must be specified even if the bandpass is pre-normalized.
bandpass_weights *= u.Unit("K_RJ") # Specify K_RJ or K_CMB
bandpass_frequencies *= u.GHz

model.remove_dipole() # Remove the dipole from the CMB component
emission = model(
    freqs=bandpass_frequencies, 
    weights=bandpass_weights, 
    fwhm=0.8*u.deg, 
    output_unit="mK_RJ",
)

hp.mollview(emission[0], hist="norm") # Plotting the intensity
plt.show()

Installation

cosmoglobe can be installed via pip

pip install cosmoglobe

Funding

This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No 776282 (COMPET-4; BeyondPlanck), 772253 (ERC; bits2cosmology) and 819478 (ERC; Cosmoglobe).

License

GNU GPLv3

cosmoglobe's Projects

c3pp

A Commander3 post processing tool.

commander

Commander is an Optimal Monte-carlo Markov chAiN Driven EstimatoR which implements fast and efficient end-to-end CMB posterior exploration through Gibbs sampling.