Dwarf Spheroidal Galaxies : From observations to models and vice versa. Yves Revaz

Transcription

1 Dwarf Spheroidal Galaxies : From observations to models and vice versa Yves Revaz

2 The good reasons to study dsphs : Test for the LCDM paradigm : small structures are predicted in abundance Galaxy luminosity function Bower et al. 2003

3 The good reasons to study dsphs : The missing satellite problem LCDM simulations predict the existence of a high number of dwarf galaxies orbiting around Andromeda and the MilkyWay......but only a modest population is observed. Via Lactea (Diemand et al. 2007) Simon & Geha 2007

4 The good reasons to study dsphs : In the hierarchical LCDM paradigm, dsphs are the building blocks of larger objects Dwarf galaxies Spiral galaxies time Elliptical galaxies Galaxy clusters

5 The good reasons to study dsphs : Much more complex than usually thought Tinguely 1970

6 Agenda What is a dsph galaxy? How do we model these objects? The driving parameters Intrinsic or extrinsic evolution? Can we predict the stellar mass for a given halo mass Some conclusions

7 What is a dsph galaxy? Faint stellar system (Mv < -15) Low velocity dispersion (~10 km/s) Evidence for dark matter No clear rotation (dominated by random motions) No ongoing star formation No gas (or at least not detected) [Fe/H] follows luminosity

8 clustered around spiral galaxies dsphs are interior to transition systems, themselves interior to dirrs Mateo 2008

9 diffuse objects core core tidal tidal Fornax Carina Piatek, 2007; 2003

10 they form a sequence Adapted from Tolstoy, Hill & Tosi 2009

11 ...but are also very different Sculptor Carina Vt=198 ±50 km/s Vr=79 ±6 km/s Peri : 68 kpc (33, 83) Apo :122 kpc (97,133) Period : 2.2 Gyr Vt=85 ±39 km/s Vr=22 ±24 km/s Peri : 20 kpc (3, 63) Apo :102 kpc (102,113) Period : 1.4 Gyr today today Piatek et al. 2006, 2003

12 disparate, structures, diff. stellar pop as fct of r Carina Time Rizzi et al also Tolstoy et al. 2004; Battaglia et al Out In Star Formation Rate Sculptor Time

13 What is at the origin of the diversity? Is the environment the driving parameter? Chance encounters produce a variety of properties Can we think otherwise? How much of the variety is intrinsic? When and how is interaction required? Sequence = single framework of formation?

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15 Current limitations Too simplistic chemical evolution Arbitrary fixed SFH Small number of simulations Evolution stopped at high z Confront results only with global relations

16 Global relations are not all... Objects with very similar : - Lv - [Fe/H] - [M/Lv]...

17 ... may have completely different stellar and chemical properties! SFR, M* AGE [Fe/H] [Mg/Fe]

18 Observations : Where do we stand? Accurate abundances measurement from individual stars for: Fornax Sculptor Sextans Carina Team DART (Letarte et al. 2010) (Hill et al. in prep.) (Shetrone et al., 2001, Aoki et al.,2009, Jablonka et al., in prep.) (Koch et al., 2008, Lesmale et al., 2011, Venn et al., in prep.)

19 Modelisation Code & physical processes The initial conditions Tests and Robustness

20 GEAR : a self-consistent Tree/SPH code (Revaz & Jablonka 2012) Skeleton : Gadget-2 (Springel 2005) Gravity : -> treecode (Barnes & Hut 86) NlogN instead of N2 Hydrodynamics : -> SPH : Smooth Particles Hydrodynamics (Lucy 77, Gingold & Monaghan 77) Hydrodynamics values are obtained by convolution of neighbors particles with a kernel function the resolution follows the mass

21 GEAR : a self-consistent Tree/SPH code The baryon physics Cooling function (metal dependent) : - above 104K (Sutherland & Dopita 93) - below 104K, H2, HD, OI, CII, SiII, FeII (Maio et al. 07) Star formation : classical recipes : Schmidt law (Schmidt 59) (Katz 92) + star formation density (0.1 a/cm3) + starformation temperature (3x104K)

22 GEAR : a self-consistent Tree/SPH code Chemical evolution SSP scheme : (Poirier 03, PhD thesis) - SNIa, SNII nucleosynthesis + feedback from SN explosions - elements followed : Fe, Mg

23 Time Kodama & Arimoto 97 Formation time of a stellar particle (SSP) mass fraction yields energy Injection into the system : nearest neighbors IMF : Krupa 01

24 SNII : yields of massive stars (Iwamoto et al. 99) Energy : esn 1051 ergs/sn (thermal)

25 SNIa : model from Kobayashi et al yields from Tsujimoto et al. 95, updated models Energy : esn 1051 ergs/sn (thermal)

26 Outputs of models and observables stellar particles : Fe, Mg, Z, age -> Lv (Vasdekis et al. 96) gas particles : Fe, Mg, Z, density, temperature all particles : positions, velocities, mass

27 Initial conditions

28 Initial conditions - 2 Mpc/h3 box, dark matter only (WMAP V) - 134'217'728 particles => resolution of 150 pc/h, Msol/h more than 150 dsph haloes with masses between 108 > M > 109 Msol

29 Z=

30 Z=

31 50% of the haloes have their density profiles already in place at z=6 (in physical coordinate) 98% have an NFW profile, wich central densities varying by a fractor ~3 only (for masses between 108 and 109 Msol)

32 Initial conditions : isolated models Models of dsphs in a static Euclidean space, where the expansion of the universe is neglected, are justified. The physics of baryons that depends on the density in physical coordinates is correct. The densities of haloes with mass between 108 and 109 Msol exhibit a small dispersion, a factor 3 to 4, which could help understanding the variety in the observed properties of the dsphs Core profile supported by the observations (Blais-Ouellette et al. 2001; de Blok & Bosma 2002; Swaters et al. 2003; Gentile et al. 2004, 2005; Spekkens et al. 2005; de Blok 2005; de Blok et al. 2008; Spano et al. 2008)

33 Energy conservation, Robustness & Convergence tests

34 9.5x108Msol Conservation better than 5% over more than 250 dynamical times!

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36 chemical properties : - metallicity distribution - abundances density profile

37 Results

38 Parameters (see also Revaz et al. 2009) More than 400 simulations, Exploring the effect of the parameters

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40 Efficiency of supernova energy : Mass = 4x108Msol esn= 100% esn= 1% If esn=100% (1051 ergs per SN) no Fe/H enhancement (need to be below 10%) no strong winds : the gas is kept around the system 107 Msol of gas linked to the dsph (see also Marcolini et al. 06, Valcke et al. 08)

41 Mass or density? density x 5 : Δ[Fe/H]= 1.0 dex mass x 9 : Δ[Fe/H]= 0.5 dex density c*=0.05 esn=0.03 Cooling stronger for larger densities Mass increases luminosity but has negligible impact on the chemical evolution mass

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43 Fornax 7x108Msol Sculptor 8 5x10 Msol Sextans 8 3x10 Msol Carina 8 1x10 Msol

44 Do we observe a sequence? Yes The dominant driving parameters are the mass and density (compatible with the cosmology) More massive and dense systems, forms stars continuously high [Fe/H] high Lv Less massive and less dense sytems forms stars episodically low [Fe/H] But we need outer physical processes to truncate the star formation to get rid of the remaining gas low Lv

45 Metallicity gradients Sextans (Battaglia et al. 2011) Fornax (Battaglia et al 2006) Sculptor (Tolstoy et al. 2004)

46 Metallicity gradients metalicity gradients?

47 Metallicity gradients : the effect of gas motion High resolution model : M= Msol, 4x106 of particles hot gas heated by SNs accumulates at the center due to strong Archimedes forces this gas is driven outside high metallic gas is ejected into the IGM ( Msol)

48 Metallicity gradients : the effect of gas motion High resolution model : M= Msol, 4x106 of particles

49 How galaxies populates their dark matter halo?

50 Abundance matching Millennium Simulation (MS; Springel et al. 2005) High resolution MS (Boylan-Kolchin et al. 2009) SDSS/DR7 Assume main subhaloes and satellite subhaloes have galaxies at their centres, Guo et al the stellar masses of these galaxies are directly related to the maximum dark matter mass ever attained by the subhalo during its evolution. In practice, this mass is usually the mass at z= 0. one-to-one and monotonic relationship between Mhalo and M* n(>mhalo) = n(>m*)

51 Abundance matching : Sawala et al 2011 SDSS+Millenium Guo et al 2010 Extrapolation Sawala et al 2011

52 Abundance matching Sawala et al 2011 SDSS+Millenium Guo et al 2010 Who is right? Who is wrong?

53 Faber-Jackson / Tully-Fisher relation SDSS+Millenium Guo et al 2010

54 Faber-Jackson / Tully-Fisher relation SDSS+Millenium Guo et al 2010

55 Faber-Jackson / Tully-Fisher relation SDSS+Millenium Guo et al 2010

56 Can we find 10 km/s stellar systems in Msol halos?

57 Large sample of halo populated by stars with random properties (N-body systems) Halo : generalized NFW (HonhSheng Zhao 1996, Treu et al. 2002) CUSP or CORE Mh : [108,1011] Msol rs,h : [0.5-4] kpc h : [0,1] Stars : generalized NFW Mh : [105,109] Msol rs,s : [0.5-4] kpc s : [0,1] Velocities computed from the Jeans Equations

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59 Baryonic fractions at odd with plausible star formation histories bf : [3x10-5, 3x10-4] bf : [3x10-4, 3x10-3] Maccio et al Carina-like Fornax-like

60 Conclusions GEAR : a self-consistent Tree/SPH code for dsphs simulations robust + good convergence In LCDM, the density profiles of small haloes does not evolve much betweeen z=6 and z=0 Possible to study dsph in an isolated context To fit the metallicity of dsphs, the feedback efficiency cannot be large : no strong winds but a large amount of gas left Global relations are reproduced But also the variety in stellar populations and chemical abundances for : Fornax, Sculptor, Sextans & Carina

61 Conclusions Evolution driven by : Intrinsic processes : mass+density Extrinsic processes : get rid of the remaining gas + truncate the SFR Credit : Olivier Tiret Tidal stripping? Ram pressure stripping? The low stellar content predicted by LCDM for 10 10Msol seems to be incompatible with our models

62 The futur of GEAR Cosmological simulations dirr and spiral galaxies

63 The End