Astrophysics Source Code Library

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Searching for codes credited to 'Dunkley, Jo'

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[ascl:1704.007] PySM: Python Sky Model

PySM generates full-sky simulations of Galactic foregrounds in intensity and polarization relevant for CMB experiments. The components simulated are thermal dust, synchrotron, AME, free-free, and CMB at a given Nside, with an option to integrate over a top hat bandpass, to add white instrument noise, and to smooth with a given beam. PySM is based on the large-scale Galactic part of Planck Sky Model code and uses some of its inputs.

[ascl:2001.010] CosMOPED: Compressed Planck likelihood

CosMOPED (Cosmological MOPED) uses the MOPED (Multiple/Massively Optimised Parameter Estimation and Data compression) compression scheme to compress the Planck power spectrum. This convenient and lightweight compressed likelihood code is implemented in Python. To compute the likelihood for the LambdaCDM model using CosMOPED, one needs only six compression vectors, one for each parameter, and six numbers from compressing the Planck data using the six compression vectors. Using these, the likelihood of a theory power spectrum given the Planck data is the product of six one-dimensional Gaussians. Extended cosmological models require computing extra compression vectors.

[ascl:2307.012] mnms: Map-based Noise ModelS

mnms (Map-based Noise ModelS) creates map-based models of Simons Observatory Atacama Cosmology Telescope (ACT) data. Each model supports drawing map-based simulations from data splits with independent realizations of the noise or equivalent, similar to an independent set of time-domain sims. In addition to the ability to create on-the-fly simulations, mnms also includes ready-made scripts for writing a large batch of products to disk in a dedicated SLURM job.