Measuring the Mass of a Galaxy: An Evaluation of the Performance of Bayesian Mass Estimates Using Statistical Simulation

• Activity Number: 175
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Gwendolyn Eadie*+
• Companies: McMaster University
• Keywords: incomplete data ; astrophysics ; galaxy ; dark matter ; mass profile ; bayesian

Abstract

A common way to estimate the mass of a galaxy is to observe the kinematics of objects orbiting it, and then infer the mass by assuming a model for the gravitational potential and mass distribution. We use a simulation approach to study biases that may occur when kinematic data are used in this way. Data sets are simulated from two different velocity distributions and then each set is analysed, either with complete velocity vectors (complete data) or without complete velocity vectors (incomplete data), using a Bayesian isotropic Hernquist (1990) model. We investigate three scenarios: (1) the model and data come from the same probability distribution function (PDF), (2) the model and data come from the same PDF and the data is incomplete, and (3) the model and data come from different PDFs and the data is incomplete. No biases were found in scenarios 1 and 2, but a positive bias was found in scenario 3. The cause of the bias in the latter scenario appears to be caused by the isotropic Hernquist model incorrectly interpolating for the incomplete data.