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CosMOPED: Compressed Planck likelihood

Posted: Fri Jan 31, 2020 12:42 am
by Ada Coda
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 one-dimensional Gaussians. Extended cosmological models require computing extra compression vectors.

Credit: Prince, Heather; Dunkley, Jo

Site: https://github.com/heatherprince/cosmoped
https://ui.adsabs.harvard.edu/abs/2019PhRvD.100h3502P

Bibcode: 2020ascl.soft01010P

Preferred citation method: Please see citation information here: https://github.com/heatherprince/cosmoped#please-cite

ID: ascl:2001.010