Hydro ART simulations sample

Transcription

1 Hydro ART simulations sample Stellar Merger Trees Dylan Tweed Racah Institute of Physics, HUJI, Jerusalem CANDELS Theory Workshop - UCSC - August 8 th 10 th 2012 D. P. Tweed Racah Institute 8/8/ / 18

2 of ART simulations. Collaborators, Daniel Ceverino, Nir Mandelker, Adi Zolotov, Marcello Cacciatto, Loren Hoffman, Avishai Dekel, Joel Primack. AMR simulation hydro ART, (Kratsov, Klypin), 30 zoom-in simulations of high redshift galaxies, spatial resolution kpc. Main focus, VDI, disc evolution, bulge formation. D. P. Tweed Racah Institute 8/8/ / 18

3 Intro section Sample Galaxy Target Mv Rv Mv Mstar Mg afin M kpc M M M MW MW MW MW MW MW MW MW MW MW MW VL VL VL VL VL VL VL VL VL VL VL VL SFG SFG SFG SFG SFG D. P. Tweed Racah Institute 8/8/ / 18

4 Gas mosaics D. P. Tweed Racah Institute 8/8/ / 18

5 Gas mosaics D. P. Tweed Racah Institute 8/8/ / 18

6 Gas mosaics D. P. Tweed Racah Institute 8/8/ / 18

7 Gas mosaics D. P. Tweed Racah Institute 8/8/ / 18

8 Overview D. P. Tweed Racah Institute 8/8/ / 18

9 Pipeline 1 Group finding on stellar component: Galaxies, clumps. 2 Merger trees. 3 : Galaxy evolution, In-situ clump, Ex-situ clump (mergers/interactions) D. P. Tweed Racah Institute 8/8/ / 18

10 AdaptaHOP AdaptaHOP: group-finder algorithm, inspired from SUBFIND and HOP Written in 2003 by Stéphane Colombi. Incorporated to SAM GalICS (Galaxies In Cosmological Simulations) from 2005 as part of the Horizon Project ( PI: Romain Teyssier) Also used to detect clumps in AMR zoom-in simulations Ramses (Devriendt) ART (Tweed). D. P. Tweed Racah Institute 8/8/ / 18

11 Basic idea Gets a SPH density for each particle n closest neighbors Oct-tree scheme. Groups particles around local density maxima. Maps those maxima in a structure tree. Defines galaxies and clumps from the hierarchy of density peaks. Note: Galaxies and clumps are not stripped of unbound particles. D. P. Tweed Racah Institute 8/8/ / 18

12 Selection of clumps candidates Number of particles: mass thresholding. shape selection ρ max α > < ρ node >, size r > r ɛ. Removing Poisson noise, < ρ node > > ρ t [1 + fudge/ N] Only topological, no unbinding. D. P. Tweed Racah Institute 8/8/ / 18

13 Mapping the halo internal structure Symbols: filled: local maxima, open: local saddle point Density distribution= groups of particles around maxima connected by saddle points. D. P. Tweed Racah Institute 8/8/ / 18

14 Mapping the halo internal structure Symbols: filled: local maxima, open: local saddle point First density thresholding, cut haloes from the background. ρ t = 80 < ρ DM > analog to FOF b=0.2. D. P. Tweed Racah Institute 8/8/ / 18

15 Mapping the halo internal structure Symbols: filled: local maxima, open: local saddle point Separating local maxima into nodes by increasing density of saddle points D. P. Tweed Racah Institute 8/8/ / 18

16 Mapping the halo internal structure Symbols: filled: local maxima, open: local saddle point Separating local maxima into nodes by increasing density of saddle points D. P. Tweed Racah Institute 8/8/ / 18

17 Mapping the halo internal structure Symbols: filled: local maxima, open: local saddle point Some density peak might not be isolated as node (low number of particles, Poisson noise) D. P. Tweed Racah Institute 8/8/ / 18

18 Merger trees 1 Star particles used as tracer. 2 One descendent per galaxy/clump 3 In-situ clump: no progenitor detected as the separate galaxy. 4 Ex-situ clump: at least one progenitor detected as a separate galaxy. 5 merger fraction. D. P. Tweed Racah Institute 8/8/ / 18

19 Clump finding, clump tracking. a=0.37 D. P. Tweed Racah Institute 8/8/ / 18

20 Clump finding, clump tracking. a=0.37 D. P. Tweed Racah Institute 8/8/ / 18

21 Clump finding, clump tracking. a=0.38 D. P. Tweed Racah Institute 8/8/ / 18

22 Clump finding, clump tracking. a=0.38 D. P. Tweed Racah Institute 8/8/ / 18

23 Clump finding, clump tracking. a=0.39 D. P. Tweed Racah Institute 8/8/ / 18

24 Clump finding, clump tracking. a=0.39 D. P. Tweed Racah Institute 8/8/ / 18

25 Clump finding, clump tracking. a=0.40 D. P. Tweed Racah Institute 8/8/ / 18

26 Clump finding, clump tracking. a=0.40 D. P. Tweed Racah Institute 8/8/ / 18

27 Clump finding, clump tracking. a=0.41 D. P. Tweed Racah Institute 8/8/ / 18

28 Clump finding, clump tracking. a=0.41 D. P. Tweed Racah Institute 8/8/ / 18

29 Clumps co-rotating with the disc. Visualization in the rotation frame of the galaxy 1 Smooth component + In-situ clumps + Ex-situ clumps 1 j z = L star.l gal and j max = r star v star D. P. Tweed Racah Institute 8/8/ / 18

30 Clumps co-rotating with the disc. Visualization in the rotation frame of the galaxy 1 Smooth component + In-situ clumps 1 j z = L star.l gal and j max = r star v star D. P. Tweed Racah Institute 8/8/ / 18

31 Clumps co-rotating with the disc. Visualization in the rotation frame of the galaxy 1 Smooth component 1 j z = L star.l gal and j max = r star v star D. P. Tweed Racah Institute 8/8/ / 18

32 3 criteria classification 1 structural decomposition: (Clump finder), smooth, In-situ clumps, Ex-situ clumps 2 kinematic decomposition: stellar halo, stellar bulge, stellar disc. 3 Stellar origin: (merger trees), star is born in the halo, bulge or disc component, born in a In-situ clump, born ex-situ (merger fraction) D. P. Tweed Racah Institute 8/8/ / 18

33 3 criteria classification Classification scheme Smooth In-situ clumps Ex-situ clumps H B D H B D H B D born in halo born in bulge born in disc born in clump : <f<1: :30<f<1: :10<f<1: :3<f D. P. Tweed Racah Institute 8/8/ / 18

34 3 criteria classification Useful fraction for Bulge( j=1) Disc (j=2) µ IsDisc (j) = 2 k=0 m(2jk)/ ( 7i=0 2k=0 m(ijk) ) µ IsClump (j) = 2 k=0 m(3jk)/ ( 7i=0 2k=0 m(ijk) ) µ Ex situ (j) = ( 7i=4 2k=0 m(ijk) ) / ( 7i=0 2k=0 m(ijk) ) µ f>10 (j) = ( 7i=6 2k=0 m(ijk) ) / ( 7i=0 2k=0 m(ijk) ) µ 3 (j) = ( 2k=0 m(7jk) ) / ( 7i=0 2k=0 m(ijk) ) µ IS (j) = 7 i=0 m(ij1)/ ( 5i=0 2k=0 m(ijk) ) D. P. Tweed Racah Institute 8/8/ / 18

35 Stellar fractions D. P. Tweed Racah Institute 8/8/ / 18

36 Stellar fractions D. P. Tweed Racah Institute 8/8/ / 18

37 Stellar fractions D. P. Tweed Racah Institute 8/8/ / 18

38 Stacked evolution D. P. Tweed Racah Institute 8/8/ / 18

39 Stacked evolution D. P. Tweed Racah Institute 8/8/ / 18

40 1 A sample of 30 high redshift galaxies. (Same cosmology, resolution) D. P. Tweed Racah Institute 8/8/ / 18

41 1 A sample of 30 high redshift galaxies. (Same cosmology, resolution) 2 Same Postprocessing pipeline Group-finding on stars Merger-trees. In-situ, Ex-situ discrimination from merger tree D. P. Tweed Racah Institute 8/8/ / 18

42 1 A sample of 30 high redshift galaxies. (Same cosmology, resolution) 2 Same Postprocessing pipeline Group-finding on stars Merger-trees. In-situ, Ex-situ discrimination from merger tree 3 Further analysis Extra kinematic decomposition. Detailled stellar tracking according to both structural decomposition and kinematic decomposition. Define global measure and properties. D. P. Tweed Racah Institute 8/8/ / 18

43 1 A sample of 30 high redshift galaxies. (Same cosmology, resolution) 2 Same Postprocessing pipeline Group-finding on stars Merger-trees. In-situ, Ex-situ discrimination from merger tree 3 Further analysis Extra kinematic decomposition. Detailled stellar tracking according to both structural decomposition and kinematic decomposition. Define global measure and properties. 4 What s to be done. DM merger trees Gas inflow (wet mergers disc instabilities) D. P. Tweed Racah Institute 8/8/ / 18

44 1 All the simulations, post analysis are on the Jerusalem cluster. The wiki is a guide to find the data there. 2 Upgrade and advertise the wiki with mosaics. 3 Share and enjoy Make the stellar merger trees available. (standard format, what would you need?) Provide DM merger trees as well. D. P. Tweed Racah Institute 8/8/ / 18