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The Marenostrum Numerical The Marenostrum Numerical

Cosmology Project Cosmology Project

-MNCP- -MNCP-

Gustavo Yepes Gustavo Yepes

Universidad Autónoma de Madrid Universidad Autónoma de Madrid

http://astro.ft.uam.es/marenostrum http://astro.ft.uam.es/marenostrum

(2)

The MareNostrum The MareNostrum

Numerical Cosmology Project Numerical Cosmology Project

The MNCP is an international collaboration of different institutions The MNCP is an international collaboration of different institutions

spread across the world with the aim of producing state-of-the-art spread across the world with the aim of producing state-of-the-art

Grand Challenge Cosmological Simulations Grand Challenge Cosmological Simulations of structure formation in the Universe.

of structure formation in the Universe.

This collaboration was established after the installation of the

Marenostrum supercomputer in

Barcelona in 2004 in which most of

the simulations have been done

(3)

People behind MNCP

(P.I.)Stefan Gottlöber (AIP)

(P.I. )Gustavo Yepes

(UAM)

(4)

MNCP

• In this collaboration, we use state-of-the art parallel MPI numerical codes to treat simultaneously:

• Gravity using N-body solvers

• Gas dynamics: SPH and AMR

• Cooling and heating from atomic processes

• Star formation and stellar feedbacks

(5)

MNCP

All codes are fully MPI parallel using different domain decomposition techinques:

Fully Lagrangian codes:Fully Lagrangian codes:

GADGET (TREEPM + SPH)

GASOLINE ( TREECODE + SPH)

GRID BASED CODE with Adaptive Mesh refinement GRID BASED CODE with Adaptive Mesh refinement techniques:

techniques:

Adaptive Refinement Tree (ART)

(6)

MNCP FIRST MNCP SIMULATION WAS DONE DURING THE TESTING PERIOD OF MARENOSTRUM I (2004-2005)

THE MARENOSTRUM UNIVERSE

Still the world’s largest gasdynamical SPH simulation of

large scale structure formation in the Universe

(7)

The The MareNostrum Universe MareNostrum Universe TREEPM+SPH simulation TREEPM+SPH simulation

Concordance cosmological Model

1,500 Million light-years computational box

GADGET 2 code (Springel 2005)

Adiabatic SPH+TREEPM Nbody

10243 FFT for the PM force.

15 kpc force resolution.

2x10243 dark and sph particles

109.33 partículas

8x109 M dark matter

109 M for gas particles

1 million dark halos bigger than

a typical galaxy (1012 Mo)

Simulation done at MareNostrum 1 (2005)

512 processors (1/20th total power)

1Tbyte RAM

500 wallclock hrs (29 cpu years)

Output: 8600 Gbytes of data.

(8)

The The MareNostrum Universe MareNostrum Universe TREEPM+SPH simulation TREEPM+SPH simulation

Movie:

Movie:

The time evolution of the gas component at the position of the largest

galaxy cluster formed in the simulation.

Colors

correspond to logarithm of the gas density

(9)

The The MareNostrum Universe MareNostrum Universe TREEPM+SPH simulation TREEPM+SPH simulation

ovieovie: A fly-by : A fly-by through the through the

simulation box.

simulation box.

The movie The movie shows the shows the

density of gas density of gas

color coded color coded according to according to

logarithm of the logarithm of the

density density..

(10)

MNCP

Most computationaly expensive simulation done up to now by MNCP:

THE MARENOSTRUM HIGH-Z GALAXY FORMATION SIMULATION

After more than 2 centuries of CPU time the simulation has just evolved a patch of universe from an age of few hundred

million years to few billion years, still too young compared with its present age.

(11)

The MareNostrum High-z The MareNostrum High-z

GALAXY FORMATION SIMULATION GALAXY FORMATION SIMULATION

Gasdynamics and N-body with 2 billion particles

+

Detailed modelling of baryonic physics.

To study in detail the galaxy formation process we need to account at least for To study in detail the galaxy formation process we need to account at least for

Radiative and Compton coolingRadiative and Compton cooling

UV-photoionizationUV-photoionization

Multiphase ISM.Multiphase ISM.

Star Formation.Star Formation.

Star-Gas backreactionsStar-Gas backreactions..

Use Springel-Hernquist (2003) implementation of multiphase SPH modeling Use Springel-Hernquist (2003) implementation of multiphase SPH modeling

in GADGET-2.

in GADGET-2.

(12)

z = 5.6 z = 5.6

MareNostrum galaxy formation simulation MareNostrum galaxy formation simulation

Box 1.5x106 light-years 2x 109 particles gas+dark ΛCDM model

Mgas=1.4 x106 Msun Mdark=107 Msun.

Mhalos > 109 Msun Picture:

A slice of Gas density

(13)

z = 5.6 z = 5.6

MareNostrum galaxy formation simulation MareNostrum galaxy formation simulation

Box 50/h Mpc 2x 10

9

gas+dark

LCDM model Mgas=1.4 x10

6

Msun

Mdark=10

7

Msun.

Mhalos > 10

9

Msun

Mass Function:

Abundance of galaxies when the Universe was 1/3 of its

present age

z = 11.2

z = 11.2 z = 7.3z = 7.3

(14)

z = 5.6 z = 5.6

MareNostrum galaxy formation simulation MareNostrum galaxy formation simulation

Picture of the Simulation taken from the light coming from stars formed in the simulated volume. Note the enormous amount of tiny objects much smaller than present day galaxies. These are the protogalaxies that will eventually form the present day galaxies by mergers.

his is a mock CCD image a big-enough telescope could take from the real universe proviided it could point to the same position in the sky for more than 10

6

seconds

(15)

CODE COMPARISON

MNCP GADGET (SPH) MNCP GADGET (SPH)

800 processors of MN Resolution: 500 pc.

400 YEARS of CPU

http://astro.ft.uam.es/marenostrum

HORIZON -RAMSES (AMR) HORIZON -RAMSES (AMR)

More than 2000 processors Resolution: 2 kpc

150 YEARS CPU

http://www.projet-horizon.fr

(16)

MNCP

Projects under development:

High resolution simulations of the formation and High resolution simulations of the formation and

evolution of evolution of

Clusters and Groups of Galaxies Clusters and Groups of Galaxies

A different approach:

Select a representative sample of galaxy groups and clusters from a large box and resimulate them with very accurate

physics and resolution

(17)

Adaptive multi-mass to achieve high resolution:

Re-Simulated areas from large

computational boxes by resampling

particles of increasing mass away from the refined region:

Original initial conditions up to 40963 particles in a big box.

Trace back particles of selected objects to identify

region to be resimulated with very high resolution

Very easy way of parallelization.

(18)

GALAXY CLUSTERS

ART eulerian Nbody+

Hydro code :

A Kravtsov & D. Rudd

(19)

ART Cluster Sample

2 4 0 M p c/ h

Low Resolution simulation produced sample of ~250

groups and clusters

Run using 128 Marenostrum processors using a total of

30k CPU hours

5123 particles, over 2 billion

AMR grid cells

(20)

High-Resolution Re-simulations

3.6 Mpc/ h

13 most massive

objects

re-simulated at high mass & spatial

resolution (~5-7 kpc, 7.5x108 M☉)

1-2 million particles,

~40 million grid cells per cluster

Run using 384 Marenostrum

processors using 340k CPU hours in

the past year

(21)

High-Resolution Re-simulations

Dark Matter

Gas

Stars

(22)

High-Resolution Re-simulations

Dark Matter

Gas

Stars

z = 1 z = 0.5 z = 0

(23)

SIMULATING GROUPS OF GALAXIES :

1 CODES used:

2 GASOLINE and GADGET 3 In collab. with R. Feldmann

and L. Mayer (Zurich)

(24)

Galaxy Groups

Bound structures with masses 10

12

-10

14

M

, typically up to ~50 observable galaxies, sizes ~ 1 Mpc; likely dominant place of Galaxy evolution

(25)

Set-up of the simulations

TreeSPH code Gasoline (Wadsley et al. 2004)

Collisionless DM particles, Eq. of Motion solved efficiently with a Tree-Code

Gas component followed with Smooth Particle Hydrodynamics (SPH), a particle-based Lagrangian formulation of the Euler-equations

Star formation, SN feedback, UV-background, metal enrichment

Initial conditions Several layers of different resolution

• SPH particles only in the highest-res region

x1 x8 x64

grafic-2

(26)

Simulation Runs at the MN

Sim Remark CPUh Proc

G2-VHR-DM Group G2; DM-only; very high resolution 60’000 128 G2-hE-hF SPH; 2x standard softening; high feedback 30’000 64

G2-hE-lF SPH; 2x standard softening; low feedback 30’000 64 G2-hT SPH; high initial gas temperature, high time

resolution

60’000 64

G1 Group G1 (isolated group) 64’000 128

G3 Group G3 (near cluster) 250’000 128

Sum ~500’000

memory allocation of all runs except G2-VHR-DM: ~16 GByte memory allocation of G2-VHR-DM (estimated): ~100 GByte

in total 3 Groups: G1-G3

(27)

Central galaxies

High-z galaxies:

Observations indicate evolved stable disks at z~2-3, with high SFR (Foerster-Schreiber et al. 2006, Genzel et al. 2006, Stark et al. 2008

)

What do self-consistent Hydrodynamical simulations predict?

We are currently studying our high-z central

galaxies:

high SFR ~ 30 Msol/yr at z~2.5

(but less than the Genzel et al. 2006 object ~140 Msol/yr, but the uncertainty on the latter is huge +->80 Msol/yr)

Central object has a cold-gas disk of

~3kpc radius. M~5x10^9 Msol at z=2.5.

(left) Face-on, (right) Edge-on

z=2.5

Feldmann et al. in prep

(28)

Satellite Galaxies

We see indeed the action of the group environment!

Merging

Tidal tails Ram-pressure

500 kpc (com)

gas star

z=2.5

Edge-on view on disk. DM (blue), stellar (red) and cold gas (green).

The stripping of the gas disk is clearly visible.

The group at z~2. Tidal streams from mergers between satellites and the central object are visible.

A high-redshift merger between gaseous disks

(29)

Galaxy Group Formation

Movie: This movie shows the time evolution of one of our

galaxy group objects

simulated with GASOLINE at high resolution. We display the sum of dark matter (blue),

stars (red) and gas(green) is displayed

(30)

SIMULATING OUR OWN LOCAL GROUP

WE LIVE HERE

(31)

Constrained Simulations of the Constrained Simulations of the

Local Universe Local Universe

The perfect tool to study the formation of individual objects, that look like those close to us, starting from cosmological initial conditions and in a realistic environment.

Eg. Virgo, Coma, the Local filament .. or the Local Group.

An excellent laboratory to investigate how dark matter

is distributed and structured in a similar environment

than our own galaxy .

(32)

Observational Constrains Observational Constrains

Mass and velocity constrains Masses of nearby X-ray clusters

Reiprich & Bohringer 2002 Peculiar Velocities taken from

MARK3, SBF (large scale)

(YH, Klypin,Gottlober,Kravtsov ,2002)

+

Karantchenstev et al. ( LG) Cosmological Model:

WMAP3 parameters

(33)

Simulated Volumes Simulated Volumes

Box 160/h Mpc:

CS: 2563 density field

COMA, LSC, PP, GA, Virgo

Resimulated box with much higher

resolution:

Make random realization of LCDM P(K) in a 40963 mesh.

Substitute fourier modes corresponding to those from the 2563 CR.

Apply Zeldovich approx to find displacement fields

Fill box with arbitrary number of particles up to the 40963 maximum.

COMA

G.A. P-P

LSC

(34)

Simulated Volumes Simulated Volumes

Box 160/h Mpc:

CS: 2563 density field

COMA, LSC, PP, GA, Virgo

Our biggest runs:

Our biggest runs:

10243 particles filling the box 1.2 kpc, 2.5x108 Msun Resimulated area around LSC

40963 particles (4x106 Mʘ), 300 pc resolution.

300 million particles total.

ART N-body code.

COMA

G.A. P-P

LSC

(35)

Simulating the Local Universe

Simulations including observational constrains in the initial conditions from the distribution of galaxies in our neighbourhood (R <100Mpc) can reproduce the mass structures observed around us

300 kpc

250K Msun:

40963 effective particles ~ 7x1010 in

whole box.

Only 60 million with zoomed

simu.

(36)

Galaxy formation in the LG

• Overall, the Local Group object found in the constrained simulation looks quite realistic

Environment, internal dynamics, halo structures

It can be used as a cosmological lab for galaxy formation to It can be used as a cosmological lab for galaxy formation to test different modeling of the various baryonic processes:

test different modeling of the various baryonic processes:

(“gastrophysics”) and compare results with observations:

(“gastrophysics”) and compare results with observations:

Disk structure, Star formation history, HI and metal distributions, Local UV sources, surviving satellites

(37)

Disk galaxies in DM halos

(38)

Effects of baryons on dark halos

M31

DM only

40963 res

DARK MATTER DENSITY

(39)

Effects of baryons on dark halos

M31

GAS+DM+STARS

20483 res

Adiabatic Compression More compact dark mater halos Spherical objects

(40)

Indirect Dark Matter Detection

Make simulated maps of γ -ray detection by FERMI (former GLAST)

Study effects of substructure

Signal from nearby galaxies in the LG.

Better than Via Lactea simulation because we include baryons

.

LG 20483 Dark Matter Only

LG 20483 dark + baryons

(41)

NATURE OF THE DARK MATTER NATURE OF THE DARK MATTER

cold or warm ? cold or warm ?

M

wdm

=3 keV M

wdm

=2 keV

M

wdm

=1 keV

RESIMULATING THE Local Group in a different

cosmological setting:

WDM particles:

Mwdm = 3keV – 1 keV Comparison with ΛCDM:

•density profiles

•substructure mass functions

(42)

MILKY WAY IN CDM vs WDM

Counting the number of

substructures

surviving within the halos and

comparing with those found in the Milky Way, one can put limits to the mass of the particles

composing the dark matter:

(43)

THE MISSING SATELLITE THE MISSING SATELLITE

PROBLEM PROBLEM

CDM vs WDM CDM vs WDM

Λ WDM 3keV Λ WDM 1keV Λ CDM

Constraints on the Mass of the dark matter

particle from simulations: M > 3kev

(44)

SUMARIO SUMARIO

La Creación de Universos Virtuales realistas en una de las herramientas La Creación de Universos Virtuales realistas en una de las herramientas fundamentales para considerar a la Astrofísica y la Cosmología como fundamentales para considerar a la Astrofísica y la Cosmología como

verdaderas ciencias experimentales:

verdaderas ciencias experimentales:

Es el laboratorio natural donde hacer experimentos con las componentes del universo y sus interacciones físicas.

Nos permite adentrarnos en épocas todavía no accesibles a la observación y predecir que podemos esperar ver.

Las simulaciones cosmológicas son uno de los desafíos computacionales más Las simulaciones cosmológicas son uno de los desafíos computacionales más

importantes. Debido a que la gravedad es una fuerza no saturante, es muy difícil derivar importantes. Debido a que la gravedad es una fuerza no saturante, es muy difícil derivar

algoritmos capaces de distribuir los elementos computacionales que describen los algoritmos capaces de distribuir los elementos computacionales que describen los

distintos fluidos de forma eficiente entre miles o decenas de miles de procesadores distintos fluidos de forma eficiente entre miles o decenas de miles de procesadores

Es necesario realizar un trabajo de desarrollo de códigos paralelos considerable. Es necesario realizar un trabajo de desarrollo de códigos paralelos considerable.

El paralelismo en este campo está en sus comienzos, menos de 10 años de vida…El paralelismo en este campo está en sus comienzos, menos de 10 años de vida…

Grid super-computing puede ayudar a resolver el problema..Grid super-computing puede ayudar a resolver el problema..

The The

MareNostrum Numerical Cosmology ProjectMareNostrum Numerical Cosmology Project, pretende unir esfuerzos a nivel , pretende unir esfuerzos a nivel internacional para abordar problemas de

internacional para abordar problemas de grand challenge grand challenge que necesitan de capacidades que necesitan de capacidades computacionales extremas y de recursos humanos suficientes para el análisis de los

computacionales extremas y de recursos humanos suficientes para el análisis de los datos numérico

datos numéricos.s.

(45)

GRACIAS POR SU ATENCIÓN GRACIAS POR SU ATENCIÓN THANKS FOR YOUR ATTENTION THANKS FOR YOUR ATTENTION

http://astro.ft.uam.es/marenostrum [email protected]

[email protected]

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