CosMOPED: Compressed Planck likelihood
Abstract
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 onedimensional Gaussians. Extended cosmological models require computing extra compression vectors.
 Publication:

Astrophysics Source Code Library
 Pub Date:
 January 2020
 Bibcode:
 2020ascl.soft01010P
 Keywords:

 Software