Estimation of line-of-sight velocities of individual galaxies using neural networks – I. Modelling redshift–space distortions at large scales
Hongxiang Chen,
Jie Wang,
Tianxiang Mao
et al.
Abstract:We present a scheme based on artificial neural networks (ANNs) to estimate the line-of-sight velocities of individual galaxies from an observed redshift–space galaxy distribution. We find an estimate of the peculiar velocity at a galaxy based on galaxy counts and barycentres in shells around it. By training the network with environmental characteristics, such as the total mass and mass centre within each shell surrounding every galaxy in redshift space, our ANN model can accurately predict the line-of-sight ve… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.