DARK ENERGY UNIVERSE SIMULATION,

DARK ENERGY UNIVERSE SIMULATION, The first-‐ever full observable Universe simulaDons. DEUS ConsorDum www.deus-‐consorDum.org J.-‐M. Alimi, V. Bouillot, Y. Rasera, V. Reverdy, P.-‐S. CorasaniD, I. Balmes Jean-‐Michel ALIMI Dark Energy Universe SimulaDon •  The Cosmic expansion is accelerated •  What is the nature of the Dark Energy that drives this acceleraDon ? Probably, the most challenging problem in Cosmology, in Physics. •  How can we disDnguish between DE Models ? •  What can we learn on DE from LSS FormaDon ? / •  How LSS formaDon process is affected by the presence of Dark Energy Developping the largest cosmological DM simula9ons to date with realis9c DE component, involving billions of par9cules, highest spa9al resolu9on for the largest set of simulated Universe, our challenge is to reproduce with unprecedented details the cosmic structure forma9on process and answer to these fundamental ques9ons both from theore9cal point of view and by providing useful results for the present and future cosmological surveys as SDSS, Planck, DES, Euclid, … DEUS Series DEUS Full Universe Runs: The first-‐ever full observable Universe Simula9ons: LCDM , DE dynamical models. DEUS FUR Jean-‐Michel ALIMI Dark Energy Universe SimulaDon •  ObservaDonal Evidences of Dark Energy / Nature of Dark Energy •  What can we learn on DE from LSS FormaDon ? -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ •  How should we proceeded to perform numerical simulaDon of structure formaDon in presence of Dark Energy ? −  RealisDc DE Models −  DEUS-‐CHALLENGE Applica9on: OPTIMISATION ! − IniDal CondiDons, N-‐Body simulaDons, Post Processing Workflow -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ •  Dark Energy Universe SimulaDon Series (DEUSS) •  Dark Energy Universe Simula9on Full Universe Run : First-‐Ever Full Observable Universe Simula9ons (DEUS FUR) •  DEUS in the interna9onal Context •  Numerous DEUSS and DEUS FUR Chalenges and Results •  Dynamical Aspect: Non linear imprint of DE on LSS, Non Universality on Mass FuncDon… •  StaDsDcal Aspect: Origin of Bulk Flow, Origin of halos profils… •  Some preliminary results for DEUS FUR •  ProspecDve…. LIA/DEUS Project ? Jean-‐Michel ALIMI ObservaDonal Evidences of “Dark Energy” Jean-‐Michel ALIMI ObservaDonal Evidences of “Dark Energy” Cosmic complementarity
The Concordance Model ΛCDM Baryons ~ 5%
CDM ~ 25%
Dark Energy ~ 70%
Kowalski et al. 2008
Jean-‐Michel ALIMI Radiations
~ 0.01%
Cosmological Paradigm   Covariance Principle   Equivalence Principle   Cosmological Principle New energy-‐component (ρ) + to LM and DM: ViolaDon of the strong energy condiDon }
The Hypothesis “Einstein’s General RelaDvity is the standard model of gravitaDon” is conserved The Cosmological Principle is discussed Standard Model and theoreDcal extensions New vision of the Universe: LT SoluDon, Averaged inhomogeneous Universes. There are numerous proposed models of dark energy ! Jean-‐Michel ALIMI How can we discriminate between all Dark Energy Models ? Can Large Scale Structure secle the Dark Energy debate?   New constraints on Dark Energy from Large Scale Structure FormaDon   Criteria for detecDng w(z) (at z>>1)   PredicDons on Large Scale Structure from alternaDves to ΛCDM Large scales (linear regime) / Small Scales (non-‐linear regime) Jean-‐Michel ALIMI Numerical Simula&ons (CDM only, here) with corresponding H(a),… DM FIELD, DM HALOS, DM EVOLUTION Constraints from observa&onal data (SNe Ia, CMB, BAO,… ) → ΩM (ΩCDM ,ΩΒ), ΩQ , σ8 REALISTIC COSMOLOGICAL MODELS THEORETICAL INTERPRETATIONS THEORETICAL PREDICTIONS AND OBSERVATIONAL CONSTRAINTS … Linear MaTer Power Spectrum at z=0 and Linear growing modes D+(a) → INITIAL CONDITIONS ` at zstart Theore&cal approaches to DE (QUINTESSENCE, Phantom Fluid Model, Coupled Models, « AWE/ Non universal ST Gravity », f(R), …) → a(t), H(t), φ(t,x), D+(a) , G(t), … Jean-‐Michel ALIMI Realistic Dark Energy Dynamical Models (RDEM).
Cosmological constant ΛCDM:
wΛ = −1.
Quintessence scenari: DE as a Violation of the strong energy condition
€
w DE
=
PDE
ρ DE
ϕ˙ − V (ϕ)
= 2˙
ϕ + V (ϕ)
2
Ratra-Peebles (1998) potential (SUSY breaking, backreactions, …) RPCDM
Sugra potential (radiative correction of RPCDM at E~mPl) SUCDM
⎛ λ4 +α ⎞
λ4 +α
€
VRP (ϕ) = α VSU (ϕ) = ⎜ α ⎟ exp( 4 πGϕ )
ϕ
⎝ ϕ ⎠
Phantom fluid dark energy model (modification of gravity, k-essence…) : W’CDM
€
w PFDE = −1.2
€
Jean-‐Michel ALIMI RQM: From ObservaDonal Data to Cosmological Parameters Likelihood analysis of the combined SNIa UNION dataset and WMAP data. Flat Universe, CAMB modified to take into account δQ clustering. RPCDM Klypin et al 2003 SUCDM Maio et al 2006 RealisDc Models (DEUSS) (Alimi et al 2010) Dolag et al 2004 •  Constraints on Ωm et Ω(Λ,Q) from Union SNe Ia data set (Kowalski et al 2008) •  Constraints on Ωb,ΩCDM,σ8 from WMAP5 (Komatsu et al 2008). Conclusion Low slope, Ωmh2 slightly lower than in ΛCDM •  ΛCDM vs QCDM’s: frozen vs dynamical DE •  RPCDM vs SUCDM: varying w(z) (/w constant) Jean-‐Michel ALIMI RPhM: From ObservaDonal Data to Cosmological Parameters (DEUS FUR) 1 and 2σ likelihood contours in the
w-Ωm (top panel) and w-σ8 (bottom panel)
planes respectively.
The solid lines corresponds to
marginalized limits from WMAP7-yr data,
while the red-yellow contours in the top
panel are from the UNION dataset.
The symbols corresponds to
RPCDM (+), ΛCDM-W7 (x) and wCDM (o).
With this choice of cosmological parameters the two non-‐standard dark energy models exhibit a linear growth of the density perturbaDons that is specular relaDve to that of the concordance model. Jean-‐Michel ALIMI Realistic Quintessence Models: Cosmological parameters table: DEUSS
Parameters ΛCDM RPCDM SUCDM H0 (km/s/Mpc) 72 72 72 Ωcdm 0.26 0.23 0.25 Ωbh2 0.02273 0.02273 0.2273 σ8lin 0.8 0.66 0.73 α
0 0.5 1 λ(eV)
2.4 x 10-‐3 4.9 2.1 x 103 AS 2.1 x 10-‐9 2.0 x 10-‐9 2.1 x 10-‐9 ns 0.951 0.951 0.951 w0 -‐1 -‐0.87 -‐0.94 w1 0 0.08 0.19 Flat Universe ΩΛ,Q=1-Ωm
(WMAP5)
Jean-‐Michel ALIMI Realistic DE Dynamical Models: Cosmological parameters table: DEUS FUR
Parameters ΛCDM RPCDM W’CDM H0 (km/s/Mpc) 72 72 72 Ωcdm 0.2573 0.23 0.2750 Ωbh2 0.02258 0.02273 0.2258 σ8lin 0.801 0.66 0.852 ns 0.963 0.963 0.963 w0 -‐1 -‐0.87 -‐1.2 w1 0 / 0 Flat Universe ΩΛ,Q=1-Ωm
(WMAP7)
Jean-‐Michel ALIMI DEUS-CHALLENGE Application: From Observation, Initial Conditions,
N-Body simulation, Post Processing of Numerical data.
Jean-‐Michel ALIMI Sosware ImplementaDon -‐ High resoluDon N-‐Body simulaDons RAMSES_DEUS: a fully threaded tree-based (Khokhlov 98) AMR code with PM solver (Teyssier, 2002)
Cartesian mesh refined on a cell by cell basis
octs: small grid of 8 cells, pointing towards
1 parent cell
6 neighboring parent cells
8 children octs
Multigrid method for Poisson equation (Guillet & Teyssier 2011)
Time integration using recursive sub-cycling
Parallel compuDng using the MPI library, Domain decomposiDon using « space filling Peano-‐Hilbert curves », (Gadget) Very Good scalability up to 76032 nodes on Curie Supercomputer Memory and Communica9on op9misa9ons are crucial (DEUS FUR) Cosmological rouDnes modified for Dark Energy
Jean-‐Michel ALIMI Sosware ImplementaDon – OPTIMISATIONS (memory and communica9on) Efficiency of N-‐body/Poisson solver as a funcDon of the number of MPI tasks in a weak-‐scaling configuraDon. The reference corresponds to 74 MPI tasks. The efficiency is shown at the beginning of the run (yellow), at 1/4th (red), half (purple), 3/4th (blue) and at the end of the run (green). . The efficiency is first of the order of 60%, it falls to about 55% during a short Dme when the first refinements are triggered and finally it increases to 75%. MulDgrid acceleraDon allows us to reach higher efficiencies comparaDvely to the efficiency of an ideal PM-‐FFT code in black. Jean-‐Michel ALIMI Sosware ImplementaDon – OPTIMISATIONS Mean memory usage as a funcDon of number of MPI tasks in a weak-‐scaling configuraDon: beginning of the run (orange), at 1/4th (red), half (purple), 3/4th (blue) and at the end of the run (green). The control of memory usage (including the one from MPI buffers) achieved at the 5% level was a key point for the success of the run. Jean-‐Michel ALIMI Sosware ImplementaDon – OPTIMISATIONS WriDng speed as a funcDon of number of MPI tasks: green is for 100 KB files, purple 1 MB, red 10 MB, yellow 100 MB, black 1 GB like in our run. This is measured using a benchmark on less than 128 nodes. Blue points correspond to the average wriDng speed during the whole Full Universe Run (4752 nodes/38016 MPI tasks), and the weak scaling simulaDons. The token system was tuned to saturate the bandwidth allocated for our simulaDons Jean-‐Michel ALIMI Sosware ImplementaDon – OPTIMISATIONS Efficiency of programs developed to process data generated during the DEUS FUR simulaDon as a funcDon of the number of MPI tasks. The efficiency obtained is saDsfactory: The computaDon of the power spectrum for validaDng the results of RAMSES-‐DEUS using the applicaDon POWERGRID-‐DEUS is the green curve. The redistribuDon of these data along the Peano-‐Hilbert curve in cubic spliyng by applying Slicer applicaDon is the blue curve. The detecDon of massive halos by the percolaDon algorithm ”Friends of Friends” is performed by applying pFoF-‐DEUS, its efficiency is represented by the red curve. Jean-‐Michel ALIMI Dark Energy Universe SimulaDons Series: A large set of simulaDons Large set of Universe Volumes (+ 25 simula9ons), Very High spa9al resolu9on: 2.5 h-‐1 kpc to 10.4 h-‐1Gpc (21 h-‐1Gpc ), Very High mass resolu9on: 2.5 1010 h-‐1 M⦿ to more than 1016 h-‐1M⦿ Halos Ini9al redshid deep in linear regime Jean-‐Michel ALIMI Dark Energy Universe SimulaDons Series: A large set of simulaDons Large set of Universe Volumes (+ 25 simula9ons), Very High spa9al resolu9on: 2.5 h-‐1 kpc to 10.4 h-‐1Gpc (21 h-‐1Gpc ), Very High mass resolu9on: 2.5 1010 h-‐1 M⦿ to more than 1016 h-‐1M⦿ Halos Ini9al redshid deep in linear regime Jean-‐Michel ALIMI Dark Energy Universe SimulaDons Series LARGE SET OF UNIVERSE VOLUMES (+ 25 SIMULATIONS), HIGH SPATIAL RESOLUTION AND MASS: 2.5 h-‐1 kpc to 10.4 h-‐1 Gpc, 2.5 108 h-‐1 M⦿ to 1016 h-‐1M⦿ INITIAL REDSHIFT DEEP IN LINEAR REGIME Jean-‐Michel ALIMI Dark Energy Universe SimulaDons Series LARGE SET OF UNIVERSE VOLUMES (+ 25 SIMULATIONS), HIGH SPATIAL RESOLUTION AND MASS: 2.5 h-‐1 kpc to 10.4 h-‐1 Gpc, 2.5 108 h-‐1 M⦿ to 1016 h-‐1M⦿ INITIAL REDSHIFT DEEP IN LINEAR REGIME Jean-‐Michel ALIMI DEUS FUR The First-‐ever Full Observable Universe SimulaDon •  DEUS FUR is currently the largest and most performing dark matter simulation of the entire
cosmos ever realized probing scales from 40 h-1 kpc to 21 h-1 Gpc for the Λ CDM model. The
simulation has followed the self-gravitational evolution of 81923 (~550 billions) particles in a cubic
volume of (21 h-1 Gpc)3. Two additional simulations of non-standard dark energy models (W’CDM
and RPCDM) are progressing.
•  This simulation has required 5 million cpu hour on 76032 cores of the Curie/Bull GENCI
Supercomputer at TGCC using 304128 Go of memory. 15 Po data are generated during the three
runs. Using o uroptimized chain of post-processing programs we were able to reduce these data to
1.5 Po.
Jean-‐Michel ALIMI Dark Energy Universe SimulaDon (Mass ResoluDon) EvoluDon of the number of parDcles in N-‐body simulaDons versus Dme. D-‐symbols (red) are PM-‐AMR simulaDons made by DEUS group. We can see the acceleraDon in performance occurred in the last decade especially for DEUS collaboraDon. Note in parDcular the posiDon of the Millennium Run #10; 10 billion parDcles, box size 500 h-‐1 Mpc), the recent Millenium XXL Run #12; 303 billion parDcles, box size 3 h-‐1Gpc). and the Horizon Run #13; 375 billion parDcles, box size 10.8 h-‐1Gpc). The blue line is the mean evoluDon of the simulaDon size from Springel et al. (2005) and the dashed blue line is ”Moore’s Law” which shows a factor 2 increase every 18 months Jean-‐Michel ALIMI Dark Energy Universe SimulaDon Series: Temporal EvoluDon ΛCDM SUCDM RPCDM - z=9
- z=6.5
- z=1
- z=0.25
- z=0.
Jean-‐Michel ALIMI Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 RPCDM
ΛCDM
L = 162 h-1Mpc
L = 40 h-1Mpc
Jean-‐Michel ALIMI Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 RPCDM
ΛCDM
L = 20 h-1Mpc
L = 10 h-1Mpc
Jean-‐Michel ALIMI Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 RPCDM
ΛCDM
L = 20 h-1Mpc
L = 10 h-1Mpc
Jean-‐Michel ALIMI Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 MOVIE 1
ΛCDM Sugra Ratra-‐
Peebles Degenerate DE models at homogeneous and linear level can leave disDncDve features on the non-‐linear scales ! Jean-‐Michel ALIMI Dark Energy Universe SimulaDon: Science Challenges How DEUS (DEUSS and DEUS FUR) can be useful for ObservaDonal Projects ? Which Challenges from ObservaDonal Point of View ? How DEUS (DEUSS and DEUS FUR) can we help to becer understand the LSS formaDon process in presence of Dark Energy ? Which Challenges from TheoreDcal Point of View Jean-‐Michel ALIMI DEUS Full Universe Run: from lightcones in redshis space to Mock catalogs. •  All along the simulaDon we build the macer distribuDon in redshis space. •  ParDcle and Halos are now as we observe them not as they are at a given Dme. •  Full sky lightcones from z=0 to z≈1100, are now available. •  The distorDon in redshis space is characterisDc of the cosmology. •  From lightcone we could directly compared to present and futur cosmological surveys Jean-‐Michel ALIMI DEUS Full Universe Run: lightcones in redshis space. A very preliminary version !!! MOVIE 2
•  All along the simulaDon we build the macer distribuDon in redshis space. •  ParDcle and Halos are now as we observe them not as they are at a given Dme. •  Full sky lightcones from z=0 to z≈1100, are now available. •  The distorDon in redshis space is characterisDc of the cosmology. •  From lightcone we could directly compared to present and futur cosmological surveys Jean-‐Michel ALIMI DEUS: Imprints of Dark Energy on the non-‐linear macer power spectrum EvoluDon of the non-‐linear power spectrum in quintessence cosmologies relaDve to the ΛCDM case
RaDo of the non-‐linear power spectrum relaDve to linear predicDon for the different cosmologies as a measurement of the evoluDon of non-‐linearity in the gravitaDonal collapse. Alimi et al., DEUS ConsorDum, MNRAS 401, 775 (2010). Jean-‐Michel ALIMI DEUS: Imprints of Dark Energy on the non-‐linear macer power spectrum Alimi et al., DEUS ConsorDum, MNRAS 401, 775 (2010). Non-‐lineariDes are different for each models. The deviaDons at high k of the power spectrum are correlated with the linear growth history Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM Numerous DEUS Challenges: From TheoreDcal Point of View (2) Abnormal ObservaDonal signal on Bulk Flow in velocity surveys (Watkins et al 2008, Feldman et al 2008, Lavaux et al 2009 (2MRS survey (redshis survey)…) High deviaDon from linear predicDons. Mean of the (peculiar) velocity fields present in a sphere of radius R centered on the Milky Way Is this signal a cosmological one or is it an unlikely event? Is (Λ)Cold Dark Macer Scenario ruled out? Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM For gaussian iniDal condiDons, is such a Vbulk possible ? Is it not a rare event ? As a first approximaDon, we can characterize the Watkins curve by two data points: depleDon at 16 h-‐1 Mpc and bump at 53 h-‐1 Mpc. We then compute the Probability to get such a event from iniDal condiDon staDsDcs. Strong correlaDon between scales R16 and R53, M is the correlaDon matrix containing non-‐diagonal terms, (tail of a 2D maxwellian). P ≈ 1.4 % Watkins Vbulk could be a rare event realizaDon in ΛCDM! Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM DEUS: ΛCDM-‐WMAP5 , 10243 parDcles, 648 h-‐1 Mpc. From 20.000 random centers (environments) Using Watkins observaDonal data points: We isolate an observaDonal-‐
like sample at 95% (χ2 analysis done on all observaDonal 10 data points) : 255 out of 20.000. Rare events (P ≈1.3%) in (very good) agreement with the previous esDmaDon. Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM Watkins Bulk Flows Numerical Catalog (255) σ(R) in good agreement with linear predicDons 
VBulk (R)
seems to diverge from the linear prediction.

But VBulk (R) is directional
To solve this ContradicDon. What is the Dynamical Origin of Bulk Flow ? €
Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM We suppose such a Watkins event, What is the Dynamical Origin of Bulk Flow ? DirecDonality suggests an asymmetry in macer distribuDon. We then qualitaDvely study the direcDon of the bulk flow versus the direcDon of the center of mass; For a Watkins Numerical event, Mollweide projecDon (53 h-‐1 Mpc) Clearly dis9nct direc9on Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM We suppose such a Watkins event, What is the Dynamical Origin of Bulk Flow ? DirecDonality suggests an asymmetry in macer distribuDon. We then qualitaDvely study the direcDon of the bulk flow versus the direcDon of the center of mass; For a Watkins Numerical event, Mollweide projecDon at larger scale (85 h-‐1 Mpc) Clearly similar direc9on Jean-‐Michel ALIMI DEUS : Anomalous cosmic flow, a challenge for ΛCDM What is the Dynamical Origin of Bulk Flow ? 
Which scales shows an alignment between the We compare the mean C
(R)
for the complete Watkins bulk flow numerical catalog direcDon of asymmetry in a shell and the direcDon of the Bulk Flow at 53 h-‐1 Mpc ? and for the Linear bulk flow numerical catalog: €
~ 85 h-‐1 Mpc (bump) ~ 55 h-‐1 Mpc (depleDon) Jean-‐Michel ALIMI €



−1
VBulk (53h Mpc) . (C (R + dR) − C (R))
Alignment scale at ~ 85 h-1 Mpc
(85 = 53 + 32)
DEUS : Anomalous cosmic flow, a challenge for ΛCDM What is the Dynamical Origin of Bulk Flow ? For all events from the complete Watkins bulk flow numerical catalog, we compute the scalar product of the bulk flow at radius R with the direcDon of the asymmetry in spheres of radius R+32 

VBulk (R) . C (R + 32h −1 Mpc)
Alignment scale from 53 h-‐1 Mpc. Jean-‐Michel ALIMI €
DEUS : Anomalous cosmic flow, a challenge for ΛCDM We confirm that Vbulk is a linear quan9ty even for such a rare event. Its evolu9on sa9sfies the linear evolu9on, idem for the asymmetry factor 
VBulk (R,z) =

VBulk (R,0) =
2
⎛ D+ (z) ⎞ 2
Pδ (k,z) = ⎜
⎟ Pδ (k,0)
⎝ D+ (0) ⎠
∫ P (k,z) W (kR)dk
(H(0) f(0)) ∫ P (k,0) W (kR)dk
(H(z) f(z))
2
δ
2
2
δ
⎛ H(z) f (z)D+ (z) ⎞ 

Vbulk (R,z) = ⎜
⎟ Vbulk (R,0)
⎝ H(0) f (0)D+ (0) ⎠
€
€
€

C (R,z)

Vbulk (R,z)
€
Jean-‐Michel ALIMI €
DEUS : Anomalous cosmic flow, a challenge for ΛCDM Where is the cosmology ? Likelihood analysis on the Vbulk data for the Watkins Bulk Flow catalog
(R≤53 h-1 Mpc and R≤130 h-‐1 Mpc)
Wrong cosmological parameters (R ≤ 53 h-‐1 Mpc). Jean-‐Michel ALIMI Correct cosmological parameters (R=130 h-‐1 Mpc). DEUS : Anomalous cosmic flow, a challenge for ΛCDM •  Watkins Bulk Flow observaDons can be seen as a rare event. •  Dynamical origin of such a high Bulk Flow comes from an asymmetry of the macer at higher scales. •  There is no contradicDon with linear predicDon in (Λ)CDM •  How the mean value of the linear predicDon is recovered at higher scales should (could) be a “signature” of the Cosmology…. Jean-‐Michel ALIMI DEUS FUR The First-‐ever Full Observable Universe SimulaDon NEW HUGE SIMULATION: DEUS FULL UNIVERSE RUN •  550 billion parDcles •  2 000 billion AMR cells •  21 Gpc/h size •  From the size of the horizon to the size of the Milky Way •  LCDM, W’CDM RPCDM DEUS-‐CHALLENGE Applica9on MPGRAFIC-‐DEUS, RAMSES-‐DEUS, POST-‐
PROCESSING WORKFLOW-‐DEUS COMPUTER: CURIE THIN TGCC •  76000 cores / 300 TB memory •  3 x 5 millions cpu/hours First picture of the 3D dark macer distribuDon in redshis space resulDng from the evoluDon of the density macer fluctuaDons observed by WMAP satellite in the CDM Concordance Cosmological Model with Cosmological Constant. Jean-‐Michel ALIMI DATA : 3x 500 TB (3 x 100 000 DVD) •  ParDcles+gravity lightcones: fullsky, up to z=30 and even more by linear extrapolaDon •  15 Snapshots •  Halos in 30 snapshots •  1 billion part+cells at every Dmestep DEUS Full Universe Run : lightcones in redshis space. •  All along the simulaDon we build the macer distribuDon in redshis space. •  ParDcle and Halos are now as we observe them not as they are at a given Dme. •  Full sky lightcones from z=0 to z≈1100, are available. •  The distorDon in redshis space is characterisDc of the cosmology. •  From lightcone we could directly compared to present and futur cosmological surveys Jean-‐Michel ALIMI DEUS Full Universe Runs: Mass funcDon and cosmic variance. Jean-‐Michel ALIMI DEUS Full Universe Run: Power spectrum of dark macer •  BAO: linear and non-‐linear contribuDon. Very good staDsDcs! •  Soon to come: runs with other cosmology. Jean-‐Michel ALIMI DEUS Full Universe Runs: Power spectrum ofr DE dynamical models Jean-‐Michel ALIMI DEUS Full Universe Runs: Halos Mass FuncDon •  Number of galaxy clusters within the horizon: 340 000 in lightcone, 140 millions at z=0 •  Largest halo within the horizon: •  3 1015 Msun/h in lightcone (z ≈ 1), •  1.07 1016 Msun/h at z=0 •  Mass funcDon: strong deviaDon to Jenkins fit Jean-‐Michel ALIMI DEUS Full Universe Runs: Halos properDes Dark Macer Halos in their environment Z=0 •  FracDon of halo which is not well ficed per NFW •  This fracDon is comology and redshis dependant •  Probe of dark energy Jean-‐Michel ALIMI Profil and comparison with NFW Z=1 Dark Energy Universe SimulaDon: Open Data •  Links •  DEUS ConsorDum website hcp://www.deus-‐consorDum.org •  For the first Dme, all numerical data (fields, halos, lightcones, parDcles and gravity) from a large set of high resoluDon N-‐body simulaDons for various cosmological models with DE are (will be) available on free public database. DEUVO hcp://roxxor.obspm.fr/deuvo-‐ui/
•  Dark Energy Universe SimulaDon Series (DEUSS): •  3 dark energy cosmologies calibrated on CMB and SNIa •  Large spaDal dynamics from 3 kpc to 14 Gpc •  16 simulaDons with more than 1 billion parDcles •  Imprints of dark energy •  power spectrum: various contribuDons of DE /mass funcDon: non-‐universality •  profile: deviaDons from NFW/velocity field: staDsDcs vs cosmology •  Full Universe Run •  First simulaDon of structuring of the whole observable universe •  All galaxy clusters / very good staDsDcs for BAO •  WL, SZ galaxy clusters, Mock Catalog… •  soon: new non standard cosmologies will be completed Jean-‐Michel ALIMI Dark Energy Universe SimulaDon: LIA /DEUS ? For the first Dme, all numerical data (fields, halos, lightcones, parDcles and gravity) from a large set of high resoluDon N-‐body simulaDons for various cosmological models with DE are (will be) available on free public database. DEUVO hcp://roxxor.obspm.fr/deuvo-‐ui/ MOVIE 3
Thank you for your agen9on... Jean-‐Michel ALIMI

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