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SUMMARY:Bayesian action-based dynamical model for M31
DTSTART;VALUE=DATE-TIME:20230320T093900Z
DTEND;VALUE=DATE-TIME:20230320T094100Z
DTSTAMP;VALUE=DATE-TIME:20241114T092407Z
UID:indico-contribution-240@meetings.aip.de
DESCRIPTION:Speakers: Paula Gherghinescu (University of Surrey)\nThe posit
 ion\, velocity\, and chemical composition of each star provide clues to th
 e evolutionary history of galaxies. While the Gaia mission has offered inv
 aluable information about the Milky Way\, to understand the growth of disk
  galaxies in the Universe we must look beyond our galaxy.\n\nThe Andromeda
  Galaxy (M31) is ideal for this task thanks to its proximity (making it po
 ssible for individual stars to be resolved) and its inclination angle\, pr
 oviding a gateway to external galaxies study. Furthermore\, our position o
 utside of this galaxy is ideal for an unbiased view of its dark matter hal
 o.\n\nI am presenting a novel Bayesian action-based dynamical tool that ex
 ploits stars harvested in M31. This pipeline aims to recover parameters of
  the galaxy describing its distribution function and dark matter density p
 rofile. This will be used to understand the galaxy’s accretion history a
 nd accumulation of dark matter.\n\nAs a first test\, the pipeline has been
  applied to the Auriga simulations of M31-like galaxies. The new Bayesian 
 action-based model recovers well the parameters of the potential and of th
 e distribution function of the halos even when fitted with non-phase mixed
 \, accreted stellar data. Furthermore\, this allowed testing the equilibri
 um assumptions of galaxies and the generality with which double-power law 
 distribution functions can be used to fit stellar halo components of galax
 ies.\n\nhttps://iaus379.aip.de/event/20/contributions/240/
LOCATION:Haus H\, Telegrafenberg
URL:https://iaus379.aip.de/event/20/contributions/240/
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