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ASCL Code Record

[ascl:2207.021] BAYGAUD: BAYesian GAUssian Decomposer

BAYGAUD (BAYesian GAUssian Decomposer) implements the decomposition of velocity profiles in a data cube and subsequent classification. It uses MultiNest (ascl:1109.006) for calculating the posterior distribution and the evidence for a given likelihood function. The code models a given line profile with an optimal number of Gaussians based on the Bayesian Markov Chain Monte Carlo (MCMC) techniques. BAYGAUD is parallelized using the Message-Passing Interface (MPI) standard, which reduces the time needed to calculate the evidence using MCMC techniques.

Code site:
https://github.com/seheonoh/baygaud https://sites.google.com/view/baygaud
Used in:
https://ui.adsabs.harvard.edu/abs/2022arXiv220706698P
Described in:
https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.5021O
Bibcode:
2022ascl.soft07021O

Views: 1265

ascl:2207.021
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