Gyöngyi Kerekes Eötvös Lóránd University, Budapest MAGPOP 2008, Paris István Csabai László Dobos Márton Trencséni

 Estimate distances of stars  create 3 D maps  Explore the structure of Milky Way  Exponencial disks + power-law halo(es)  Dwarf galaxies (merging) and streams  Our goal: reproduce current distributions / find new structures  Improvements in outer regions, giants  Gaia (launch around 2011)

Colors (u-g, g-r,…) Stellar parameters (temperature, logg, [Fe/H], absolute magnitude) ? Colors (u-g, g-r,…)

Polinomial fit to main sequence: Mr=f(r-i)

 Non-parametric estimator  We use all magnitudes (colors) from SDSS  Nearest neighbors of a point in a 5D space  Weight the estimated parameters with an exponencial distribution  Can be adopted to other photometric systems

 MILES library  INDO-US library  Bright stars from SDSS  M67  NGC 2420  Total number of stars: 3392

MILES+ BaSeL  These libraries were targeted to stars with different stellar parameters  Synthetic magnitudes  Crossmatched with Hipparcos catalog  Challenges: ▪ wavelength coverage of spectra is not enough ▪ normalization of synthetic magnitudes

 No bright stars in SDSS!  Observations with Photometric Telescope (50 cm) to calibrate SDSS stars to USNO stars  Crossmatch with Hipparcos  117 stars

 First chosen as test objects  Turned out at estimation of distances that giants are overrepresented in the training set  After applying distance modulus from (Harris et al, 1996)  we added them to the TS. Extinction E(B-V) Distance modulus M (1) NGC (2) (1): Anthony-Twarog et al, 2006 (2): An et al, 2007 b.

Mr r-i

g-r Mr Blue: our estimation Red: Juric, 2008 SDSS Stripe 82 (Image coadd catalog with improved photometry) ~420,000 stars

Applying Cartesian coordinate system: Blue: our estimation Red: Juric, 2008 Z (pc) Blue: Our estimation Red: Juric, 2008

 Stripe 82 in SDSS (~420,000 stars)

 Apply to all SDSS data  Calculate metallicity  Combine with kinematics (USNO, RAVE …)  GALEX crossmatch