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Cosmological N-Body Simulation - Topology of Large scale Structure Changbom Park with Juhan Kim (Korea Institute for Advanced Study) & J. R. Gott (Princeton),

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Presentation on theme: "Cosmological N-Body Simulation - Topology of Large scale Structure Changbom Park with Juhan Kim (Korea Institute for Advanced Study) & J. R. Gott (Princeton),"— Presentation transcript:

1 Cosmological N-Body Simulation - Topology of Large scale Structure Changbom Park with Juhan Kim (Korea Institute for Advanced Study) & J. R. Gott (Princeton), J. Dubinski (CITA) CCP 2006. 8. 29

2 History of Universe

3 Theme: Origin & Formation Mechanism of Cosmic Structures 1. Want to know Origin – primordial density fluctuations from inflation Formation Mechanism – galaxies form at peaks in density field smoothed over galactic scale? 2. Time is ripe Large redshift surveys of galaxies  High precision measurements of 1. Relations among internal physical properties 1. Relations among internal physical properties 2. Relations between internal properties and 2. Relations between internal properties and spatial & temporal environments spatial & temporal environments

4 SDSS2006 CfA1986

5 SDSS galaxies h -1 Mpc (Park et al. 2005, ApJ, 633, 11)

6   Effects of NL Gravitational Evolution, Biasing, & Redshift Space Distortion on galaxy clustering & properties For PRECISION COMPARISON between cosmological models with observations Cosmological N-Body Simulation

7 Requirement for galaxy formation study 1. Several times larger than largest survey >> 1000 h -1 Mpc : for LSS formation + galaxy formation, velocity field : for LSS formation + galaxy formation, velocity field * SDSS[2006] ~ 500 h -1 Mpc * Hubble Depth S.[2015] ~ 2000 h -1 Mpc * SDSS[2006] ~ 500 h -1 Mpc * Hubble Depth S.[2015] ~ 2000 h -1 Mpc 2. Should resolve objects with <<10 11 h -1 M sun (~ M * +2) : mean separation < 0.2 h -1 Mpc : mean separation < 0.2 h -1 Mpc  currently 0.2~2000Mpc  currently 0.2~2000Mpc Number of particles > 5000 3 ~ 10000 3 will do! Number of particles > 5000 3 ~ 10000 3 will do! (100~1000 billion =10~100* current maximum) (100~1000 billion =10~100* current maximum)

8 Cosmological N-Body Simulation Dynamic range for other studies * Internal properties & environment: 1kpc ~ 100 Mpc * Internal properties & environment: 1kpc ~ 100 Mpc * Galactic structure & star formation : 0.1pc ~ 100kpc * Galactic structure & star formation : 0.1pc ~ 100kpc

9 Cosmological N-Body Simulation Progresses  ~ 10 4 CPUs  > 10 10 particles Log N=0.2(Y-1970)+2

10 TreePM Code 1 About Code 1. Long range (r>4 pixels, PM) + Short range(PM+Tree) G-forces 2. Tree generation in each slab & in each cube of 4 3 pixels 3. Min. # of particles for tree generation – Direct P 2 if #(cube) < N tree 4. Memory : ~3 x [16] x words per particle * 16 per particle: index 2, position 3, velocity 3, acceleration 3, mass 1, * 16 per particle: index 2, position 3, velocity 3, acceleration 3, mass 1, softening length, computational work measurement, pointer softening length, computational work measurement, pointer * factor ~3 for memory imbalance * factor ~3 for memory imbalance * Buffer zone particles * Buffer zone particles

11 TreePM Gravitational Force PM Tree + PM PMForce Gaussian Smoothed R G =0.9 pixels

12 TreePM Code 2 Advantages 1. O(N log N) Tree operations for short range force – unlike P 3 M 2. Periodic boundary condition solved by PM – unlike Tree 3. No need to build a global tree – force correction only out to 4 pixels 4. Local Trees  Parallelizable by domain decomposition (time)  Parallelizable by domain decomposition (time) & disposable local trees keeping trees in 8 x 8 x n z pixels (memory) & disposable local trees keeping trees in 8 x 8 x n z pixels (memory)

13 Parallelization 1. PM part 2. Tree part : Domain slabs of equal thickness : Domain slabs of equal # of : Domain slabs of equal thickness : Domain slabs of equal # of tree force interactions & tree force interactions & Buffer zone particles Buffer zone particles

14 TreePM Code 3 5. Accuracy : ~ 0.5% RMS error in acceleration for θ=1 6. Performance 6. Performance

15 CPU time per step 1024 3 particles Regular backup & Pre-halo finding calculation

16 Load balance 1024 3 particles # of particles in domain slabs / homogeneous distribution distribution

17 ΛCDM Simulations ΛCDM Simulations (Kim & Park 2004. 7) TreePM code TreePM code GOTPM (Dubinski, Kim, Park 2003) 2048 3 mesh 2048 3 mesh (initial condition) 2048 3 CDM particles 1024 & 5632 h -1 Mpc 1024 & 5632 h -1 Mpc size boxes 50 & 275 h -1 kpc 50 & 275 h -1 kpc force resolutions FOR PRECISION COMPARISON between cosmological models & real universe * Using IBM SP3 at KISTI, 128 CPUs, 900 Gbytes,

18 N-body Simulations a) b) c) a)  IBM SP3 at KISTI, 128 CPUs, 900 Gbytes, b)  IBM SP3 at SNU, 16 CPUs, c)  QUEST at KIAS, 128 CPUs, 256 Gbytes,  b =0.046

19 Growth of Structures from initial Density Fluctuations 13.7b 11.8b 7.7b t=0

20

21 Dark Halo Identification (Kim& Park 2006: ΛCDM 1024 h -1 Mpc ΛCDM 1024 h -1 Mpc ) Physically Self- Bound Halos Halo centers - local density peaks Binding E wrt local halo centers Tidal radii of subhalos wrt bigger halos Halos with >=53 particles (5x10 11 M ⊙ )

22 PSB Halos VS Others

23

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25 Topology study 1. Gaussianity of the linear (primordial) density field predicted by simple inflationary scenarios 2. Topology of galaxy distribution at NL scales sensitive to cosmological parameters & to galaxy formation mechanism 3. Direct Intuitive meaning Large Scales Small Scales Large Scales Small Scales Primordial Gaussianity Galaxy Formation Cosmological Parameters Cosmological Parameters

26 Genus – A Measure of Topology Definition Definition G = # of holes - # of isolated regions G = # of holes - # of isolated regions in iso-density contour surfaces in iso-density contour surfaces = 1/4π· ∫ S κ dA (Gauss-Bonnet Theorem) = 1/4π· ∫ S κ dA (Gauss-Bonnet Theorem) [ex. G(sphere)=-1, G(torus)=0, ] [ex. G(sphere)=-1, G(torus)=0, ] : 2 holes – 1 body = +1 Gaussian Field Gaussian Field Genus/unit volume g(ν) = A (1-ν 2 ) exp(- ν 2 /2) Genus/unit volume g(ν) = A (1-ν 2 ) exp(- ν 2 /2) where ν=(ρ- ρ b )/ ρ b σ & where ν=(ρ- ρ b )/ ρ b σ & A=1/(2π) 2 3/2 A=1/(2π) 2 3/2 if P(k)~k n, A R G 3 =[8√2π 2 ] -1 * [(n+3)/3] 3/2 if P(k)~k n, A R G 3 =[8√2π 2 ] -1 * [(n+3)/3] 3/2

27 Non-Gaussian Field (Toy models) Non-Gaussian Field (Toy models) Clusters Bubbles HDM (Weinberg, Gott & Melott 1987)

28 Non-Gaussianity: Genus-related statistics 1. Shift parameter :  2. Asymmetry parameters :A C, A V 3. Amplitude drop : R A  A obs /A PS ACAC AvAv  RARA

29 Biased Formation of Galaxies L-dependence of 1 & 2 point distribution, but also topology ! (Park et al. 2005)

30 Topology of LSS can be explained by GF models? (Park, Kim et al. 2005) Merger  Halo formation void percolation void splitting LCDM1024 Matter field can’t !

31 Topology of LSS can be explained by GF models? Direction of evolution ! ~1 & Little evolution at low z Mergers of halos A V < 1 ! = (M/M 1 ) α for M>M min where logM min =11.76, log M 1 =13.15, α=1.13 = (M/M 1 ) α for M>M min where logM min =11.76, log M 1 =13.15, α=1.13 HOD model for VL : sample M r <-19.5 (Park et al. 2005) Probably yes!

32 Comparison of topology: SDSS vs  CDM SDSS & 6 h-1Mpc scale; Kim+Park(o) & Springel(x)

33 Future of Cosmological N-Body Simulation 1. Useful for cosmology & galaxy formation study (until star formation can be properly simulated by radiative hydro-codes) (until star formation can be properly simulated by radiative hydro-codes) 2. Need to reach # of particles >> 5000 3 ~ 10000 3 (10~100 current maximum) (10~100 current maximum) Dynamic range for other studies * Internal properties & environment: 1kpc ~ 100 Mpc * Internal properties & environment: 1kpc ~ 100 Mpc * Galactic structure & star formation : 0.1pc ~ 100kpc * Galactic structure & star formation : 0.1pc ~ 100kpc


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