1 / 16

Hydrodynamical simulations of cosmic structures

Hydrodynamical simulations of cosmic structures. Stefano Borgani Department of Astronomy Inter-dept. Centre for Computational Sciences University of Trieste. Core group: Collaborators: SB (DAUT) Francesca Matteucci (staff, DAUT)

ashby
Download Presentation

Hydrodynamical simulations of cosmic structures

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hydrodynamical simulations of cosmic structures Stefano Borgani Department of Astronomy Inter-dept. Centre for Computational Sciences University of Trieste Core group:Collaborators: SB (DAUT) Francesca Matteucci (staff, DAUT) Luca Tornatore (post-doc, SISSA) Cristina Chiappini (staff, INAF) Silvia Ameglio (PhD, DAUT) Andrea Biviano (staff, INAF) Alex Saro (undergrad., DAUT) Marisa Girardi (staff, DAUT) Francesco Calura (post-doc, DAUT) Paolo Tozzi (staff, INAF) Talk @ CISC Workshop, Trieste, June 15th 2005

  2. Who are we? Basel: Ortwin Gerhard Bologna: Stefano Ettori Lauro Moscardini Mauro Roncarelli Garching: Klaus Dolag Volker Springel Trieste: Silvia Ameglio Stefano Borgani Luca Tornatore Alex Saro Beijing: Ling-Mei Cheng Padova: Giuseppe Tormen Elena Rasia Roma: Pasquale Mazzotta Torino: Magda Arnaboldi Antonaldo Diaferio Giuseppe Murante

  3. The initial conditions

  4. The final state REFLEX survey 2dF GRS

  5. What does a LSS model require? (a)Parameters of the Friedmann background (m=0.3 ; =0.7 ; H0=70+/-5 km/s/Mpc). (b) Initial fluctuation spectrum(P(k)kn with n=1). (c)Choice of fluctuation mode(adiabatic). (d)Statistical distribution of fluctuations(Gaussian). (e)Chemistry:density of baryons, cold and hot particles, number of relativistic species. (f)Tools to follow the evolution of perturbations:linear theory, approximate methods for non-linear evolution, numerical computations(N-body). (g)Relation between distributions of mass and light: evolution of gas, galaxy formation, star formation processes.

  6. The equations of motion Density fluctuation field: (a)Continuity Equation: (b)Euler Equation: (c)Poisson Equation:

  7. Evolution of hot (T> 3 keV)clusters BG ‘01

  8. N-body approaches to gravitational instability Parameters defining a simulation: 1. Box size L: ~ 1 Mpc for the formation of a single galaxy ~ 500 Mpc for the distribution of galaxies and clusters 2. Mass resolution: ~ 105-106 Msun for the formation of a single galaxy; ~108 Msun for the formation of a galaxy cluster 3. Force resolution: ~ 0.1 kpc for the formation of a single galaxy; ~ 1-5 kpc for the formation of a galaxy cluster Method 1.Direct summation Compute the force on a given particles by directly summing over the contributions of the other N-1 particles: e:softening parameter (force resolution)  N(N-1)/2 operations!!!

  9. N-body approaches to gravitational instability Method 4. Tree codes (Barnes & Hutt 1986) General strategy: Consider a far-away group of particles as a single particle for the force computation The limiting “aperture angle” =s/r regulates the accuracy of the long-range force.

  10. Smoothed particle hydrodynamics (SPH) (Monaghan 1992, ARAA, 30, 543) Use an interpolation method to express any function in terms of its values at a set of disordered points (i.e. particles): Def.: Intergral interpolant of the function A(r): W: interpolating kernel. When dealing with a discrete distribution of particles: b: particle label mb: mass of the b-th particle rb: density of the b-th particle Ab: value of A(r) at the position rb

  11. L=480 Mpc/h Ngas=NDM=4803 s8=0.8 zin=46

  12. The simulation code Tree + SPHGADGET2 (Springel et al .’01; Springel ‘05) www.MPA-Garching.MPG.DE/gadget Explicit entropy conservation (Springel & Hernquist ‘02) Radiative cooling + uniform evolving UV background Multiphase model for self-regulated star-formation Phenomenological model for galactic winds (Springel & Hernquist ‘03) Chemical enrichment from Sn-Ia and II(Tornatore et al. ’04, ‘05) Reduced-viscosity SPH scheme(Dolag et al. ‘05, in prep.)  ..... b:fraction of mass in stars>8M(Salpeter IMF) c: SN energy fraction powering winds(=0.5-1) h:amount of gas in wind, units ofdM* (=2)  vw (300-500) km s-1

  13. The simulation box(z=0) Gas density Gas temperature 40,000 CPU hours on the IBM-SP4 70 GB RAM – 1.2 TB output

  14. The biggest cluster(1.3 1015 h-1 M ) temperature field density field 9 h -1 Mpc 9 h -1 Mpc 9 h -1 Mpc

  15. Simulation of a single halo

  16. A Cluster Resimulation Champaign Extract a few (4) clusters from the box and resimulate at higher resolution Cl-2 2.9e14 M/h Cl-1 1.4e15 M/h Cl-3 2.7e14 M/h Cl-4 1.6e14 M/h

More Related