Reliable mass calculation in spherical gravitating systems. Issue 3 (29th October 2018)

• Record Type: Journal Article
• Authors: Diakogiannis, Foivos I; Lewis, Geraint F; Ibata, Rodrigo A; Guglielmo, Magda; Wilkinson, Mark I; Power, Chris
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 482:Issue 3(2019)
• Page Start: 3356
• Page End: 3372
• Publication Date: 2018-10-29
• Subjects: methods: statistical -- techniques: radial velocities -- galaxies: dwarf -- galaxies: kinematics and dynamics -- galaxies: statistics; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/sty2931
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: We present an innovative approach to the methodology of dynamical modelling, allowing practical reconstruction of the underlying dark matter mass without assuming both the density and anisotropy functions. With this, the mass–anisotropy degeneracy is reduced to simple model inference, incorporating the uncertainties inherent with observational data, statistically circumventing the mass–anisotropy degeneracy in spherical collisionless systems. We also tackle the inadequacy that the Jeans method of moments has on small data sets, with the aid of Generative Adversarial Networks: we leverage the power of artificial intelligence to reconstruct the projected line-of-sight velocity distribution non-parametrically. We show, with realistic numerical simulations of dwarf spheroidal galaxies, that we can distinguish between competing dark matter distributions and recover the anisotropy and mass profile of the system.