The cumulative mass profile of the Milky Way as determined by globular cluster kinematics from Gaia DR2

10/23/2018
by   Gwendolyn Eadie, et al.
0

We present new mass estimates and cumulative mass profiles (CMPs) with Bayesian credible regions for the Milky Way (MW) Galaxy, given the kinematic data of globular clusters as provided by (1) the Gaia DR2 collaboration and the HSTPROMO team, and (2) the new catalog in Vasiliev (2018). We use globular clusters beyond 15kpc to estimate the CMP of the MW, assuming a total gravitational potential model Φ(r) = Φ_∘r^-γ, which approximates an NFW-type potential at large distances when γ=0.5. We compare the resulting CMPs given data sets (1) and (2), and find the results to be nearly identical. The median estimate for the total mass is M_200= 0.71 × 10^12 M_ and the 50% Bayesian credible region bounds are (0.63, 0.81) × 10^12 M_. However, because the Vasiliev catalog contains more complete data at large r, the MW total mass is better constrained by these data. In this work, we also supply instructions for how to create a CMP for the MW with Bayesian credible regions, given a model for M(<r) and samples drawn from a posterior distribution. With the CMP, we can report median estimates and 50% Bayesian credible regions for the MW mass within any distance (e.g. M(r=25kpc)= 0.26 (0.24, 0.29)× 10^12 M_, M(r=50)= 0.37 (0.34, 0.41) × 10^12 M_, M(r=100kpc) = 0.53 (0.49, 0.58) ×10^12 M_, etc), making it easy to compare our results directly to other studies.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/30/2021

Bayesian Inference of Globular Cluster Properties Using Distribution Functions

We present a Bayesian inference approach to estimating the cumulative ma...
research
03/13/2020

Mass Estimation of Galaxy Clusters with Deep Learning I: Sunyaev-Zel'dovich Effect

We present a new application of deep learning to infer the masses of gal...
research
07/26/2021

From robust tests to Bayes-like posterior distributions

In the Bayes paradigm and for a given loss function, we propose the cons...
research
07/24/2023

Finite Size Effects in Addition and Chipping Processes

We investigate analytically and numerically a system of clusters evolvin...
research
11/18/2020

Bayesian mass averaging

Mass averaging is pivotal in turbomachinery. In both experiments and CFD...
research
01/04/2022

Augmenting astrophysical scaling relations with machine learning : application to reducing the SZ flux-mass scatter

Complex systems (stars, supernovae, galaxies, and clusters) often exhibi...
research
04/15/2019

Modeling Network Populations via Graph Distances

This article introduces a new class of models for multiple networks. The...

Please sign up or login with your details

Forgot password? Click here to reset