Building galaxy mocks catalogues with MICE
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1 Building galaxy mocks catalogues with MICE F. Castander, P. Fosalba, J. Carretero, M. Crocce, E. Gaztañaga, C. Bonnett, M. Eriksen, K. Hoffman, A. Bauer, S.Serrano, D. Reed, P. Tallada, N. Tonello, D. Piscia Institut de Ciències de l Espai, IEEC-CSIC, Barcelona Port d Informació Científica, PIC, Barcelona cosmohub.pic.es
2 MICE simulations Simulation process Generate large dark matter simulation Produce lightcones All-sky lensing maps generate halo catalogues produce galaxy catalogues
3 General Plan MICE simulations Build mock galaxy catalogues from N-body halos using a hybrid HOD & SHAM prescription Generate: positions, luminosities, colours and lensing Start at z=0 where constraints more stringent Constraints luminosity function colour-magnitude diagram clustering as a function of luminosity and colour Implement recipes to higher redshifts
4 Starting point Mock galaxy catalogues Large N-body MICE simulation provides halos both in the lightcone and in snapshots Use snapshots first to calibrate method then apply to lightcone Applicable to any halo catalogue
5 Mock galaxy catalogues Assign luminosities and HOD Each halo contains one central galaxy and maybe some satellite galaxies Compute how many satellite galaxies populate each halo (HOD) <N sat > = (M/M 1 ) α Assign luminosities to central and satellite galaxies conserving the luminosity function Use an abundance matching technique to obtain a relation between galaxy luminosity and halo mass Apply that relation to obtain luminosities for central galaxies
6 Mock galaxy catalogues Assign luminosities and HOD Scatter needed to fit the clustering as a function of luminosity Compute the resulting luminosity function for satellite galaxies Draw random luminosities for satellites galaxies from the LF of satellites
7 Mock galaxy catalogues
8 Mock galaxy catalogues
9 Mock galaxy catalogues
10 Mock galaxy catalogues Assign positions and velocities Centrals are placed at the center of the halos Satellites are positioned within the halos following a NFW profile using a concentration parameter: c=c(m,z) Bullock 2001, Gao2008, Munoz-Cuartas2011 Triaxial NFW are used Velocities are assigned assuming Virial equilibrium
11 Mock galaxy catalogues Assign luminosities and HOD Compute projected correlation functions and compare to observations Teak HOD parameters until a good fit is achieved NO good fit to the clustering as a function of luminosity is achieved Solutions: Scatter in the luminosity-halo mass relation More complicated HOD parameterization
12 Mock galaxy catalogues Assign positions and velocities In order to improve the fit to the clustering we need to: Change the concentration parameter as a function of luminosity Add a probability for satellites to be in a halo of a given mass as a function of the luminosity
13 Mock galaxy catalogues
14 Mock galaxy catalogues
15 Assign colours Mock galaxy catalogues Separate the galaxy population in the components: red, green and blue Fit them with Gaussians as a function of luminosity
16 Mock galaxy catalogues
17 Mock galaxy catalogues
18 Assign colours Mock galaxy catalogues We distribute centrals and satellites between these populations in a way that the clustering as a function of colour is as observed We start assigning colours to satellites We define the fraction of satellites that are red and green The fraction of blue satellites is then given The fraction of centrals that are red, green or blue are then given by the CM and the HOD
19 Mock galaxy catalogues Assign colours fsatred = f (luminosity) fsatgreen = g (luminosity) fsatblue = 1 (fsatred + fsatgreen) ftotred = fcenred * fcen + fsatred * fsat fcenred = (ftotred + fsatred * fsat) / fcen fcengreen = (ftotgreen + fsatgreen * fsat) / fcen fcenblue = 1 (fcenred + fcengreen)
20 Assign colours Mock galaxy catalogues
21 Assign colours Mock galaxy catalogues
22 Assign colours Mock galaxy catalogues Adjust the functions fsatred and fsatgreen until the clustering as a function of colour (and luminosity) is well fit to observations
23 Last steps Assign SEDs Apply to lightcone Adjust model parameters at higher z: evolutionary correction & resampling from COSMOS catalogue Assign sizes and shapes Compute SFR Compute emission lines Assign stellar masses Assign metallicity Mock galaxy catalogues
24 MICE simulations New catalogue OLD
25 New catalogue MICE simulations NEW
26 New catalogue MICE simulations NEW
27 New catalogue MICE simulations
28 MICE simulations New catalogue
29 MICE simulations Recent developments papers description: Fosalba et al 2013: arxiv: Dark Matter Crocce et al 2013: arxiv: Halo & Galaxy Catalogue Fosalba et al 2013: arxiv: Lensing Carretero et al 2014, in prep galaxy mock method I Castander et al 2014, in prep galaxy mock method II improve incompleteness: complete to i<24 to z<1.4 increase redshift range: undergoing improve SEDs: emission lines added, AGN improve lensing resolution: undergoing improve access portal: cosmohub.pic.es
30 Mock galaxy catalogues cosmohub.pic.es
31 Mock galaxy catalogues
arxiv: v2 [astro-ph.co] 15 Sep 2015
Mon. Not. R. Astron. Soc. 000, 000 000 (0000) Printed 16 September 2015 (MN LATEX style file v2.2) The MICE Grand Challenge Lightcone Simulation II: Halo and Galaxy catalogues arxiv:1312.2013v2 [astro-ph.co]
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Mon. Not. R. Astron. Soc. 000, 000-000 (0000) Printed 13 November 2014 (MN LATEX style file v2.2) An algorithm to build mock galaxy catalogues using MICE simulations J. Carretero 1,2, F. J. Castander 1,
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