2021/10/11 by Carlos López-Cobá, Li-Hwai Lin, López-Cobá, Carlos +4 · 2 citations
Computer Science · Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #Astrophysics of Galaxies (astro-ph.GA) #FOS: Physical sciences #Galaxies: Formation, Evolution, Phenomena #Statistical and numerical algorithms #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.2110.05095
openalex publication_date 2021/10/11 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
We present \XookSuut, a Python implementation of the\n\DiskFit algorithm, optimized to perform robust Bayesian inference on\nparameters describing models of circular and noncircular rotation in galaxies.\n\XookSuut~surges as a Bayesian alternative for kinematic modeling of\n2D velocity maps; it implements efficient sampling methods, specifically Markov\nChain Monte Carlo (MCMC) and Nested Sampling (NS), to obtain the posteriors and\nmarginalized distributions of kinematic models including circular motions,\naxisymmetric radial flows, bisymmetric flows, and harmonic decomposition of the\nLoS~velocity. In this way, kinematic models are obtained by pure sampling\nmethods, rather than standard minimization techniques based on the \χ2.\nAll together, \XookSuut~represents a sophisticated tool for deriving\nrotational curves and to explore the error distribution and covariance between\nparameters.\n