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GALAXIA – synthetic Galaxy model and its application to Kepler

GALAXIA – synthetic Galaxy model and its application to Kepler. Joss Bland- Hawthorn Sanjib Sharma KASC 6 Meeting Sydney, June 2013. A publicly available fast code: http://galaxia.sourceforge.net. Context.

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GALAXIA – synthetic Galaxy model and its application to Kepler

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  1. GALAXIA – synthetic Galaxy model and its application to Kepler Joss Bland-Hawthorn Sanjib Sharma KASC 6 Meeting Sydney, June 2013 A publicly available fast code: http://galaxia.sourceforge.net

  2. Context Far-field cosmologists have a "concordance model" for cleaning and comparing redshift surveys (W(α,δ); completeness; sampling; bias…) In the near field, we are far from a chemically and dynamically consistent Galactic model. But a framework for comparing surveys, analytic and N-body models is essential. • To test a hypothesis, we must understand: • Our selection function • Consequences of our selection function • Uncertainties from statistical realizations

  3. M. Ireland Friday talk

  4. A publicly available fast code: http://galaxia.sourceforge.net

  5. In the good old days, it was easy to present complex codes

  6. Sampling Analytical Model(Von Neumann rejection sampling)

  7. Adaptive Mesh (Barnes Hut Tree) Galaxia is efficient over arbitrarily large solid angles

  8. Galaxia summary • Analytical model for disc system + bulge + warp • Robin et al 2003 (Besancon model) • Stellar halo simulated using N-body simulations • Bullock & Johnston 2005 • Padova Isochrones • m >0.15 , Marigo et al 2008, Bertilli et al 1994 • 0.07<m<0.15 Chabrier et al 2000 • 3D extinction model • double exponential disc with warp and flare, hR=4.4 kpc, hz=0.088 kpc • E(B-V) at infinity match Schlegel et al 1998 or • 0.54 mag/kpc in solar neighborhood

  9. Hipparcos • V<8, r<100 pc • Difference in total number of stars, due to binarity (27%)

  10. MCMC fitting • Now we want extract new insight from a given survey. • Given a model (e.g. Galaxia), we can fit a large set of fundamental parameters to explain the observations. • We need new optimized MCMC methods to fit N model parameters with M missing data variables (marginalization) to 250,000 RAVE and 5000 GCS stars. • In the example that follows, we want to fine tune Galaxy kinematic parameters and test Gaussian DF vs. more theoretically sound DFs (e.g. Shu1969).

  11. Disk Dust Disk warp

  12. DF & asymmetric drift Shu 1969

  13. GCS-SHU

  14. RAVE-SHU

  15. G. Ricker, Friday talk: FGK dwarfs: V=4.5-13.5 M dwarfs: I < 13 All sky: 2,500,000 targets Launch: 2018

  16. Galaxia • A consistent framework is essential to progress • Results for the Kepler sample in the next talk • Powerful N-body phase space sampling and comparison not shown. In an era of Gaia, we can start to separate Galactic stars from “extragalactic stars.”

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