Speaker
Alessandro Manzotti
(The University of Chicago)
Description
CosmoSIS [http://arxiv.org/abs/1409.3409] is a modular system for
cosmological parameter estimation, based on Markov Chain Monte Carlo
(MCMC) and related techniques. It provides a series of samplers, which
drive the exploration of the parameter space, and a series of modules,
which calculate the likelihood of the observed data for a given physical
model, determined by the location of a sample in the parameter space.
While CosmoSIS ships with a set of modules that calculate quantities of
interest to cosmologists, there is nothing about the framework itself,
nor in the MCMC technique, that is specific to cosmology. Thus CosmoSIS
could be used for parameter estimation problems in other fields,
including HEP.
This presentation will describe the features of CosmoSIS and show an
example of its use outside of cosmology. It will also discuss how
collaborative development strategies differ between two different
communities: that of HEP physicists, accustomed to working in large
collaborations, and that of cosmologists, who have traditionally not
worked in large groups. For example, because there is no collaboration
to enforce a language choice, the framework supports programming in
multiple languages. Additionally, since scientists in the cosmology
community are used to working independently, a system was needed for
helping ensure that proper attribution is given to authors of
contributed algorithms.
Primary authors
Joe Zuntz
(urn:Google)
Dr
Marc Paterno
(Fermilab)
Co-authors
Alessandro Manzotti
(The University of Chicago)
Douglas Rudd
(University of Chicago)
Elise Jennings
Jim Kowalkowski
(Fermilab)
Saba Sehrish
(urn:Google)
Sarah Bridle
(UCL)
Dr
scott dodelson
(fermilab)
