Reproducing the Observed Universe with Simulations

1. Reproducing the Observed Universe with Simulations Qi Guo Max Planck Institute for Astrophysics MPE April 8th, 2008

2. Science problem: how well does the Millennium Run simulations + L-Galaxies semi-analytic model reproduce the properties of observed galaxies? • An example: study of high redshift star forming galaxies • General requirements to VO

3. Observations • Keck survey in the filters UnGR, magnitude limit • of R<25.5 with a field of view of a few hundred arcmin2 • colour-colour selection: • LBG samples (star forming galaxies at z~3): • (Un- G) > (G-R)+1.0 • (G-R) < 1.2 • BX systems (star forming galaxies at z~2) : (G-R) > -0.2 (Un- G) > (G-R)+0.2 (G-R) < 0.2(Un- G)+0.4 (Un- G) < (G-R)+1.0

4. Light Cone Survey to Mimic Observations Lightcone code SAM N-body simulation (MR) Galaxy catalogues Mock catalogue

5. Producing the right mock catalogs from the MR • precalculated lightcones in the desired filters? not available • precalculated SAM galaxy catalogs with desired filters or spectra ? not available • needed to rerun SAM to generate magnitudes in desired filters • needed to recalculate light cones in the new filter systems

6. How well can we reproduce the high redshift star forming galaxies? • Compare: • color-color diagram • redshift distribution • correlation function • number density

7. Science analysis • MR LBG sample selection identical to observed LBG samples • Mock catalogue • Steidel et al. 2004

8. Science analysis • Basic analysis: redshift distribution • Solid histograms: • from mock catalogue • (red: z~3 black: z~2) • Dashed histograms: • Steidel et al. 2004

9. Science analysis • Basic analysis: correlation function iterations: • Solid curves: • from mock catalogue • (red: z~3 black: z~2) • Region within dashed curves: correlation function within 1 sigma deviation (Adelberger et al. 2005)

10. Science analysis • Advanced analysis: Evolution (color-mass)

11. LBGs (n/arcmin^2) BXs (n/arcmin^2) literature 1.8 5.2 Mock 1 2.78 5 Mock 2 2.39 4.34 Science analysis • Iterations: • - adjust dust model, make lightcone, select new LBG sample

12. Data and codes are available for local users: Through a combination of catalogs stored at MPA, running SAM code in C, C++ programs to generate light cones, IDL scripts for sample selection, plotting, analysis

13. Data and codes are available for local users: Through a combination of catalogs stored at MPA, running SAM code in C, C++ programs to generate light cones, IDL scripts for sample selection, plotting, analysis What would be required for an outside user to perform the similar analysis using VO-like services?

14. step-by-step overview of VO-requirements 1 1 - Basic requirements • main physical parameters in halo and galaxy catalogues from • simulations • main observables for a detailed comparison with observed • samples of galaxies (e.g. magnitudes) • merger trees both for halo and galaxies • link between galaxies and their dark matter halo For high-level comparison with observations, it is essential to transform from a simulation consisting of discrete, fixed-epoch “snapshots” to a simulation in which both the physical as well as the apparent properties of galaxies evolve along the “observed” lightcone.

15. (e.g. Blaizot et al. 2005, Kitzbichler & White 2007) step-by-step overview of VO-requirements 2 2 - Making Realistic Lightcones • geometry of light cone • conversion of snapshot magnitudes to observed (apparent) magnitudes, • taking into account the proper distance modulus, K-correction, peculiar • motion and IGM attenuation towards each object along the light cone • high flexibility of generating multiple lightcones to beat down cosmic • variance

16. step-by-step overview of VO-requirements 3 3 - The simulated data must be available in the same filter system as the observed sample used for comparison • freedom of choice of the output magnitudes of the SAM catalogs for any combination of telescope+instrument+filter. This can be achieved by • making most common filters available in the VO, OR • making spectral energy distributions available in the VO, OR • allowing ``on-the-fly’’ creation of custom filtersets from the SAM

17. step-by-step overview of VO-requirements 4 • 4 - Data creation/transfer/storage • all procedures performed through remote usage of VO • The generated data need to be either stored and accessible (sql) on the VO site, or easily retrievable without running into server time-outs (within limits)

18. step-by-step overview of VO-requirements 5 5 - Sample Selection and Basic Analysis • allowing remote filtering in order to only download data of interest (e.g. by applying magnitude and colour selection criteria to the generated mock light cone observations) • and possibly, • access to online data sets generated by large galaxy surveys (e.g. SDSS, UKIDS, PAN-STARRS, HST legacy archive) with the same filtering as applied to the simulated data • ``on-the-fly’’ calculation of the main sample diagnostics (e.g. number counts, luminosity functions, redshift distributions, correlation functions) to assess basic quality of the SAM

19. step-by-step overview of VO-requirements 6 6 - Results and feedback into SAM • report the agreement/disagreement between model galaxies and observed samples • allowing ``on-the-fly’’ rerun the SAM ( e.g. parameters, models…) And, Start Over !