DARK ENERGY UNIVERSE SIMULATION, The first- ever full observable Universe simuladons.

Transcription

1 DARK ENERGY UNIVERSE SIMULATION, The first- ever full observable Universe simuladons. DEUS ConsorDum consordum.org J.- M. Alimi, V. Bouillot, Y. Rasera, V. Reverdy, P.- S. CorasaniD, I. Balmes

2 The Cosmic expansion is accelerated Dark Energy Universe SimulaDon 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

3 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?

4 ObservaDonal Evidences of Dark Energy

5 ObservaDonal Evidences of Dark Energy Cosmic complementarity The Concordance Model ΛCDM Baryons ~ 5% CDM ~ 25% Dark Energy ~ 70% Radiations ~ 0.01% Kowalski et al. 2008

6 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!

7 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)

8 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, ) Ω M (Ω CDM,Ω Β ), Ω Q, σ 8 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 z start 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),

9 Realistic Dark Energy Dynamical Models (RDEM). Cosmological constant ΛCDM: Quintessence scenari: DE as a Violation of the strong energy condition Ratra-Peebles (1998) potential (SUSY breaking, backreactions, ) RPCDM Sugra potential (radiative correction of RPCDM at E~m Pl ) SUCDM V RP ( ϕ) = λ4 +α ϕ α V SU ϕ ( ) = λ4 +α ϕ α exp 4πGϕ ( ) w Λ = 1. w DE = P DE ρ DE = ϕ 2 V ( ϕ ) ϕ 2 +V ( ϕ ) Phantom fluid dark energy model (modification of gravity, k-essence ) : W CDM w PFDE = 1.2

10 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 RealisDc Models (DEUSS) (Alimi et al 2010) Maio et al 2006 Dolag et al 2004 Constraints on Ω m et Ω (Λ,Q) from Union SNe Ia data set (Kowalski et al 2008) Constraints on Ω b,ω CDM,σ 8 from WMAP5 (Komatsu et al 2008). Conclusion Low slope, Ω m h 2 slightly lower than in ΛCDM ΛCDM vs QCDM s: frozen vs dynamical DE RPCDM vs SUCDM: varying w(z) (/w constant)

11 RPhM: From ObservaDonal Data to Cosmological Parameters (DEUS FUR) 1 and 2σ likelihood contours in the w-ω m (top panel) and w-σ 8 (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.

12 Realistic Quintessence Models: Cosmological parameters table: DEUSS Parameters ΛCDM RPCDM SUCDM H 0 (km/s/mpc) Ω cdm Ω b h σ lin α λ(ev) 2.4 x x 10 3 A S 2.1 x x x 10-9 n s w w Flat Universe Ω Λ,Q =1-Ω m (WMAP5)

13 Realistic DE Dynamical Models: Cosmological parameters table: DEUS FUR Parameters ΛCDM RPCDM W CDM H 0 (km/s/mpc) Ω cdm Ω b h σ lin n s w w 1 0 / 0 Flat Universe Ω Λ,Q =1-Ω m (WMAP7)

14 DEUS-CHALLENGE Application: From Observation, Initial Conditions, N-Body simulation, Post Processing of Numerical data.

15 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 nodes on Curie Supercomputer Memory and Communica9on op9misa9ons are crucial (DEUS FUR) Cosmological roudnes modified for Dark Energy

16 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.

17 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.

18 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

19 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.

20 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 - 1 Gpc (21 h - 1 Gpc ), Very High mass resolu9on: h - 1 M to more than h - 1 M Halos Ini9al redshid deep in linear regime

21 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 - 1 Gpc (21 h - 1 Gpc ), Very High mass resolu9on: h - 1 M to more than h - 1 M Halos Ini9al redshid deep in linear regime

22 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, h - 1 M to h - 1 M INITIAL REDSHIFT DEEP IN LINEAR REGIME

23 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, h - 1 M to h - 1 M INITIAL REDSHIFT DEEP IN LINEAR REGIME

24 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 ΛCDM model. The simulation has followed the self-gravitational evolution of (~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 cores of the Curie/Bull GENCI Supercomputer at TGCC using 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.

25 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 - 1 Gpc). and the Horizon Run #13; 375 billion pardcles, box size 10.8 h - 1 Gpc). 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

26 Dark Energy Universe SimulaDon Series: Temporal EvoluDon ΛCDM SUCDM RPCDM - z=9 - z=6.5 - z=1 - z= z=0.

27 Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 ΛCDM RPCDM L = 162 h -1 Mpc L = 40 h -1 Mpc

28 Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 ΛCDM RPCDM L = 20 h -1 Mpc L = 10 h -1 Mpc

29 Dark Energy Universe SimulaDon Series: Final StructuraDon z=0 ΛCDM RPCDM L = 20 h -1 Mpc L = 10 h -1 Mpc

30 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!

31 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

32 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

33 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

34 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 Alimi et al., DEUS ConsorDum, MNRAS 401, 775 (2010). 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.

35 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

36 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?

37 DEUS : Anomalous cosmic flow, a challenge for ΛCDM For gaussian inidal condidons, is such a V bulk 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 V bulk could be a rare event realizadon in ΛCDM!

38 DEUS : Anomalous cosmic flow, a challenge for ΛCDM DEUS: ΛCDM- WMAP5, pardcles, 648 h - 1 Mpc. From random centers (environments) Using Watkins observadonal data points: We isolate an observadonal- like sample at 95% (χ 2 analysis done on all observadonal 10 data points) : 255 out of Rare events (P 1.3%) in (very good) agreement with the previous esdmadon.

39 DEUS : Anomalous cosmic flow, a challenge for ΛCDM Watkins Bulk Flows Numerical Catalog (255) σ(r) in good agreement with linear predicdons V Bulk (R) seems to diverge from the linear prediction. But V Bulk (R) is directional To solve this ContradicDon. What is the Dynamical Origin of Bulk Flow?

40 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

41 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

42 DEUS : Anomalous cosmic flow, a challenge for ΛCDM What is the Dynamical Origin of Bulk Flow? We compare the mean C (R) for the complete Watkins bulk flow numerical catalog and for the Linear bulk flow numerical catalog: Which scales shows an alignment between the direcdon of asymmetry in a shell and the direcdon of the Bulk Flow at 53 h - 1 Mpc? ~ 85 h - 1 Mpc (bump) ~ 55 h - 1 Mpc (depledon) V Bulk (53h 1 Mpc). ( C (R + dr) C (R)) Alignment scale at ~ 85 h -1 Mpc (85 = )

43 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 V Bulk (R). C (R + 32h 1 Mpc) Alignment scale from 53 h - 1 Mpc.

44 DEUS : Anomalous cosmic flow, a challenge for ΛCDM V Bulk (R,z) = V Bulk (R,0) = We confirm that V bulk is a linear quan9ty even for such a rare event. Its evolu9on sa9sfies the linear evolu9on, idem for the asymmetry factor ( H(z) f(z) ) 2 P δ (k,z) W 2 (kr)dk ( H(0) f(0) ) 2 P δ (k,0) W 2 (kr)dk V bulk (R,z) = P δ (k,z) = H(z) f (z)d + (z) V H(0) f (0)D + (0) bulk (R,0) D + (z) D + (0) 2 P δ (k,0) V bulk (R,z) C (R,z)

45 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). Correct cosmological parameters (R=130 h - 1 Mpc).

46 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.

47 DEUS FUR The First- ever Full Observable Universe SimulaDon NEW HUGE SIMULATION: DEUS FULL UNIVERSE RUN 550 billion pardcles 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 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. COMPUTER: CURIE THIN TGCC cores / 300 TB memory 3 x 5 millions cpu/hours DATA : 3x 500 TB (3 x 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

48 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

49 DEUS Full Universe Runs: Mass funcdon and cosmic variance.

50 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.

51 DEUS Full Universe Runs: Power spectrum ofr DE dynamical models

52 DEUS Full Universe Runs: Halos Mass FuncDon Number of galaxy clusters within the horizon: in lightcone, 140 millions at z=0 Largest halo within the horizon: Msun/h in lightcone (z 1), Msun/h at z=0 Mass funcdon: strong deviadon to Jenkins fit

53 DEUS Full Universe Runs: Halos properdes Dark Macer Halos in their environment Profil and comparison with NFW Z=0 Z=1 FracDon of halo which is not well ficed per NFW This fracdon is comology and redshis dependant Probe of dark energy

54 Dark Energy Universe SimulaDon: Open Data Links DEUS ConsorDum website hcp:// 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

55 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...