|
General
|
|
Magneticum Pathfinder aims to follow the formation of cosmological structures in a so far unaccomplished level of detail by performing a set of large scale and high resolution simulations, taking into account many physical processes to allow detailed comparison to a variety of multi-wavelength observational data.
Such simulation need to incorporate a detailed description of various, complex, non-gravitational, physical processes, which determine the evolution of the cosmic baryons and impact their observational properties.
|
Cosmology
Using WMAP7 cosmology taken from Komatsu et al. 2010:
- Total matter density
=0.272
(16.8% baryons)
- Cosmological constant
=0.728
- Hubble constant
=70.4
-
Index of the primordial power spectrum n=0.963
- Overall normalisation of the power spectrum
=0.809
Physics included
- cooling, star formation, winds (Springel & Hernquist 2003)
- Metals, Stellar population and chemical enrichment
SN-Ia, SN-II, AGB (Tornatore et al. 2003/2006)
new cooling tables (Wiersma et al. 2009)
- Black Holes and AGN feedback (Springel & Di Matteo 2006, Fabjan et al. 2010)
various imrovements (Hirschmann et al. 2014)
- Thermal Conduction (1/20th Spitzer) (Dolag et al. 2004)
- Low viscosity scheme to track turbulence (Dolag et al. 2005)
various improvements (Beck et al. 2014, in prep)
- Higher order SPH Kernels (Dehnen & Aly 2012)
- Magnetic Fields (passive) (Dolag & Stasyszyn 2009)
|
|
Simulations
|
Magneticum Pathfinder & Magneticum
| Box1 | Box2 | Box3 | Box4 | Box5 |
[Mpc/h] | 896 | 352 | 128 | 48 | 18 |
mr | 2*15263 | 2*5943 | 2*2163 | 2*813 | |
hr | | 2*15843 | 2*5763 | 2*2163 | 2*813 |
uhr | | | 2*15363 | 2*5763 | 2*2163 |
xhr | | | | 2*15363 | 2*5763 |
Table 1: Number of particles used in the Magneticum Pathfinder simulations. The gray entries mark future, planned simulations.
| mdm | mgas | epsdm | epsgas | epsstars |
mr | 1.3e10 | 2.6e9 | 10 | 10 | 5 |
hr | 6.9e8 | 1.4e8 | 3.75 | 3.75 | 2 |
uhr | 3.6e7 | 7.3e6 | 1.4 | 1.4 | 0.7 |
xhr | 1.9e6 | 3.9e5 | 0.45 | 0.45 | 0.25 |
Table 2: Mass of dm and gas particles (in Msol/h) at the different resolution levels and the according softenings (in kpc/h) used.
| Box0 | Box2b |
[Mpc/h] | 2688 | 640 |
mr | 2*45363 | |
hr | | 2*28803 |
Table 3: Number of particles used in the Magneticum simulations.
|
|
Extra Runs
|
Dark Matter control simulations
We performed dark matter only control runs for various of the Boxes. To avoid a different sampling of the initial density fluctuations, all these runs where done using two dark matter particle species, e.g. by treating the gas particles as
dark matter only particles. Available dark mater only simulations include Box0/mr, Box3/hr, Box4/uhr and Box5/xhr. The imprint of teh baryonic physics on the mass function of haloes as covered by the simulation set can
be seen in the figure at the right.
MHD simulations
Currently there are varius simulations of Box3/hr as full MHD simulations available, including
simulations combining cooling and star-formation with MHD. They are probing different scenarious for the
origin of the magnetic field within the LSS.
|
|
Post processing
|
On the fly post-processing
Similar to Saro et al. (2006), we compute the luminosities of our simulated galaxies on the fly
using the stellar population synthesis model of Bruzual & Charlot (2007) in different
spectral bands (u,V,G,r,i,z,Y,J,H,K,L,M) as well as their star-formation rate and HI content.
Following Nuzza et. al. 2010 we also take dust attenuation into account when computing the
observer frame luminosities. The attenuation is estimated from the radial dust profile,
computed from the metal and HI profile of the galaxies.
Data Management
All simulations dumps have implemented an algorithm which sort the particles
among the CPUs among a space filling curve and produces an auxiliary file which
allows to identify the sub-data volume elements of any stored property among
all particle species associated to each element of the space filling curve used.
Finally there is a super index build which allos to identify the sub snapshots
which belongs to the different parts of the space filing curve.
This allows to effectively collect all data associated to a given volume
in space (defined by the elements of the space filling curve it occupies)
with a minimum of reading overhead (see figure on the right).
|
|