Galaxy clusters from cosmological hydrodynamical simulations: the intracluster medium

Transcription

1 Galaxy clusters from cosmological hydrodynamical simulations: the intracluster medium Veronica Biffi (UniTs-OATs) S. Borgani, G. Murante, E. Rasia, S. Planelles, D. Fabjan, G.L. Granato, C. Ragone-Figueroa, A.M. Beck, M. Gaspari, K. Dolag, L. Steinborn U. Maio, R. Valdarnini, M. De Petris, F. Sembolini, G. Yepes, H. Boehringer University of Ljubljana

2 Outline Motivation: why galaxy clusters? assumptions & biases the simulation approach Results Conclusions

3 Clusters of Galaxies X-ray: NASA/CXC/UA/J.Irwin et al; Optical: NASA/STScI CHESHIRE CAT CLUSTER ``Largest and latest gravitationally-bound objects in the Universe Very deep potential wells (~ Msun) Dominated in mass by DM (~80%) Baryonic content: hot gas (~15%) & galaxies (~5%) e.g. optical obs. ICM: hot gas ( K) enriched with metals emission via bremsstrahlung + emission lines very bright extended sources in X-rays

4 Why studying the ICM? Hot plasma enriched with metals (T~ K; Z~ Z sun ) traces the imprints of dynamical state, assembly and chemical history very bright extended sources in the X-rays (+ multi-wavelenght obs.) to study cluster physics ICM traces the underlying potential well allows to reconstruct the total mass (DM-dominated) scaling laws between ICM observables & total mass Chemical composition today and history interaction with other structures role of enrichment sources role of feedback processes

5 Weighting Galaxy Clusters Mass = fundamental for cosmology Dynamical methods (optical observations: weak lensing; galaxy velocity dispersions) Scaling relations (useful for high-z clusters) X-ray/SZ mass estimates based on HE Simplest assumption: ICM is in Hydrostatic Equilibrium (HE) 0= Φ 1 ρ P + spherical symmetry + purely thermal pressure support (P=P ther ) Hydrostatic Mass Estimate M HE (<r)= k BT (r)r µgm p d log ρ(r) d log r + d log T (r) d log r

6 ...but nature is more complex Abell 2589 Credits: NASA Perseus cluster Credits: NASA/CXC/Stanford/I.Zhuravleva+(2014) Bullet cluster Credits: X-ray: NASA/CXC/CfA/M.Markevitch et al.; Optical: NASA/STScI; Magellan/U.Arizona/D.Clowe et al. Several sources of possible bias: non-thermal pressure; gas motions; temperature estimation; multi-phase structure; substructures; asphericity; projection+instrumental effects

7 An helpful approach: Numerical Simulations GOALS: Simulate the evolution of the Universe and of cosmic structures (e.g. GC) Naturally obtain structures similar to those observed Predict intrinsic properties of cosmic structures and evolution with time CHALLENGES: Treat as many physical processes as possible Deal with very large dynamical ranges --- e.g. for cosmological sims of GC METHODS: Eulerian(grid) or Lagrangian(particle) approaches DM-only(gravity) or hydrodynamical(gravity + baryonic physics) Cosmological volumes or isolated objects (zoomed initial conditions) Synthetic observations: translate sims results into observational-like results

8 Gas motions Presence of gas motions that are ``non thermal (streaming, rotation, turbulence) --- can contribute to total pressure for GC hydrostatic mass estimate! VB+2011 Lau+2009 gas rotational motions in mini-halos at z>9 VB, Maio 2013 Baldi,DePetris+2016

9 XMM Sanders detectable X-ray spectral signatures: velocity broadening of heavy-ion emission lines [VB, Dolag, B öhringer 13] ATHENA phox Background: NASA/CXO; Spectrum: Hitomi Collaboration/JAXA, NASA, ESA, SRON, CSA... observing gas motions Hitomi obs. (2016)

10 The ICM multi-temperature structure XMM-Newton obs VB Kaastra phox The ICM structure is not isothermal, a complex multi-temperature structure is more representative - gas inhomogeneities - especially for NCC, disturbed clusters without AGN EM XMM-Newton obs Frank+2013

11 Temperature biases X-ray temperature under-estimates dynamical (MW) temperature VB+2016 Temperature bias is larger for high-t systems TX < Ttrue Mazzotta+2004 X-ray obs: calibration of the instrument can affect T measurement (e.g. XMM vs Chandra) N/N tot T sl T ew T mw mean(b sl ) = 0.09 mean(b e ) = mean(b m ) = b=(t X -T sim )/T sim T X /T sim T sl T ew T mw VB red Schellenberger+2015

12 Dianoga Clusters Numerical/Cosmology M 200 > 8x10 14 M sun /h M 200 ~[1-4]x10 14 M sun /h (Rasia+2015; Villaescusa+2016; VB+2016; Truong+2016; Planelles+2016) The code: Gadget-3 (extended version based on Springel 2005) improved SPH hydro-scheme w/ artificial diffusion (Beck+2015) new AGN-feedback model (Steinborn+2015)

13 Galaxy Clusters: classifications Dynamical: regular/relaxed vs. disturbed ~round no significant substructures X-ray peak coincides with BCG pressure support is essentially thermal Core properties: cool core (CC) vs. non-cool core (NCC) many substructure recent or undergoing merging gas distribution displaced wrt DM signatures for gas shocks etc. X-ray central peak metallicity profiles peaked at center and steeper profiles low central gas entropy low-temperature high-density gas at the center lower central metallicity and flatter profile central entropy core higher entropy level at the center higher temperature in the core In most cases CC clusters are also regular, while NCC are disturbed. However, the two classifications not necessarily correspond 1:1

14 CC/NCC populations (see Leccardi+2010; Rossetti+2011) IN : r<0.05r 180 OUT : 0.05R 180 <r<0.2r 180 central entropy pseudo-entropy Sims. naturally generate CC and NCC populations CC ~30% at z=0 agreement with observed entropy profiles CC Pratt+2010 NCC Pratt+2010 Rasia+2015

15 Entropy-Metallicity Relation AGN - EW Leccardi+10 AGN: projected, EW anti-correlation agrees with observations Z Fe,IN /Z Fe,sun [2D] similar slope (~10% less) mildly higher normalization (~13%) smaller scatter 0.2 CC 0.0 VB+(in prep.) σ [2D] 1 NCC Clusters with low central entropy are also the most metal-rich

16 Chemical properties of the ICM ZF [Fe] e/zf e, VB+(in prep.) BH2015/091 CC NCC Leccardi & Molendi (2008) r/r 180 ZF e/zf e, Broad agreement with data CC profiles more peaked at the center NCC profiles flatter and lower central metallicity Both relatively smooth at large radii CC Ettori+2015 ZF e/zf e, NCC Ettori+2015 Rasia+2015

17 ZSi/ZFe(solar) [Si/Fe] BH2015/091 CC NCC AWM7 (Sato et al. 2008) Centaurus (Sakuma et al. 2011) Coma (Matsushita et al. 2013) ZO/ZF e(solar) [O/Fe] BH2015/091 CC NCC AWM7 (Sato et al. 2008) Centaurus (Sakuma et al. 2011) VB+(in prep.) r/r r/r 180 Relatively flat abundance ratios, especially for r > 0.1 R180 SNII and SNIa products are distributed similarly no clear distinction between CC and NCC Suggests early-enrichment: gas pre-enriched at high z has mixed and z=0 distribution appears homogeneous

18 CC/NCC pressure profiles Planelles+2016 CC: higher central pressure than NCC (Arnaud+2010; McDonald+2014) AGN sims consistent with obs. results

19 Mass bias: CC/NCC b M = (M HE -M true )/M true CC-NCC R2500 R500 R200 For similar depth of the potential well, CC have larger thermal pressure support than NCC in the core --> smaller mass bias b M =(M HE M)/M r/r vir Mass bias: no strong dependence on large-scale dynamical state, except in the very outskirts b M = (M HE -M true )/M true VB+2016 dyn r/r vir

20 HE-deviation ( δ HE ) HE: 0 = dv dt = Φ 1 ρ P = a = a G + a H Considering the radial components, δ HE = G r /H r +1

21 HE-deviation ( δ HE ) & Mass bias Average mass-bias <20% out to R 200 (~20% for T sl ) M-bias <10% within the core (< R 2500 ) Large scatter in the outskirts Mass bias HE-deviation Average HE-deviation within 20% Median stacked profile tracing massbias out to R 200 b M = (M HE -M true )/M true G r /H r r/r vir R 200 δ HE = G r /H r +1 VB r/r vir

22 HE-deviation central entropy pseudo-entropy (see Leccardi+2010; Rossetti+2011; Rasia+2015) CC-NCC CC/NCC: no separation in the level of HE-violation dynamically regular clusters: less deviation from HE than disturbed ones severe lack of HE in outskirts of disturbed clusters: accretion of substructures, significant gas motions etc. regular clusters: (see Neto+2011; Meneghetti+2014) G r /H r G r /H r dyn r/r vir r/r vir VB+2016 dynamical classification is more useful than cool-coreness to single out lack of HE

23 Conclusions Galaxy clusters are fundamental crossroads for astrophysics & cosmology Multi-wavelength obs. crucial to study physical properties & to accurately determine mass cosmology X-ray powerful to observe clusters up to high z & for scaling relations need for precise mass calibration ICM traces DM potential well and formation history of GCs Combine observations and numerical simulations to interpret great amount of upcoming data & make predictions Advanced cosmological hydrodynamical sims of GCs with AGN-feedback: naturally obtained CC/NCC populations and reproduce several observed properties at z=0 trustable to make predictions on intrinsic properties & redshift evolution