Probing the Growth of Structure in the Outskirts of Galaxy Clusters

Probing the growth of structure in the outskirts of galaxy clusters

Dominique Eckert

Department of Astronomy, University of Geneva Istituto di Astroﬁsica e Fisica Cosmica, Milano

Main collaborators: S. Molendi, S. Paltani, S. Ettori, F. Vazza, M. Roncarelli, M. Jauzac, J.-P. Kneib, M. Rossetti, F. Gastaldello, S. De Grandi, M. Gaspari, E. Pointecouteau, G. Hurier, ...

D. Eckert May 4, 2015 Outline

Structure formation at work: The outskirts of galaxy clusters Thermodynamic properties of clusters at large scales Baryon content of galaxy clusters Accretion of group-scale halos Filaments and the missing baryons Conclusion

D. Eckert May 4, 2015 Galaxy Clusters: Introduction

Millenium Simulation, Springel et al. 2005

D. Eckert May 4, 2015 Galaxy Clusters: Introduction

Jenkins et al. 2005

D. Eckert May 4, 2015 Galaxy Clusters: Introduction

Briel et al. 2001

D. Eckert May 4, 2015 The plasma emits X-rays through thermal bremsstrahlung and line emission

1/2 ε ∼ T ne nH + lines

The X-ray emission is (roughly) proportional to the squared gas density

The Intracluster medium (ICM)

Contains most of the baryons (∼90%) High-temperature plasma (T ∼ 107 − 108 K) Low densities (∼ 10−3 cm−3)

Briel et al. 2001

D. Eckert May 4, 2015 The Intracluster medium (ICM)

Contains most of the baryons (∼90%) High-temperature plasma (T ∼ 107 − 108 K) Low densities (∼ 10−3 cm−3) The plasma emits X-rays through thermal bremsstrahlung and line emission

1/2 ε ∼ T ne nH + lines Briel et al. 2001

The X-ray emission is (roughly) proportional to the squared gas density

D. Eckert May 4, 2015 The SZ eﬀect is proportional to the Compton y parameter:

σT Z y = 2 ne (`)kTe (`)d` me c

The SZ eﬀect is proportional to the integrated thermal pressure of the gas

The Sunyaev-Zel’dovich eﬀect

Galaxy clusters are optically thin and permeated by the CMB The CMB spectrum is modiﬁed along the LOS of a cluster

D. Eckert May 4, 2015 The Sunyaev-Zel’dovich eﬀect

Galaxy clusters are optically thin and permeated by the CMB The CMB spectrum is modiﬁed along the LOS of a cluster The SZ eﬀect is proportional to the Compton y parameter:

σT Z y = 2 ne (`)kTe (`)d` me c

The SZ eﬀect is proportional to the integrated thermal pressure of the gas

D. Eckert May 4, 2015 (Pseudo-)entropy −2/3 K = Tne indicates the state of the gas CC trace relaxed clusters, NCC dynamically active

Thermodynamic properties

Cluster classiﬁcation following X-ray properties: “Cool-core” or “Non-cool core”

Leccardi et al. 2010

D. Eckert May 4, 2015 Thermodynamic properties

Cluster classiﬁcation following X-ray properties: “Cool-core” or “Non-cool core” (Pseudo-)entropy −2/3 K = Tne indicates the state of the gas CC trace relaxed clusters, NCC dynamically active

Pratt et al. 2010

D. Eckert May 4, 2015 The outskirts of galaxy clusters

3 Why pushing toward the outskirts? (R > R500) Contain ∼ 90% of the volume and ∼ 50% of the mass!

Understand the build-up of galaxy clusters

Search for the ﬁlaments of the cosmic web

Estimate the global baryon budget Roncarelli et al. 2006 Fig. 1 Simulated galaxy cluster. The white circles indicate r500,r200,rvir, and 3 r200 moving outwards, respectively (adapted from Roncarelli et al. 2006). Left: X-ray surface brightness in the soft (0.5–2) keV band. The color scale spans 16 orders of magnitude and has been chosen to highlight cluster outskirts. Right: Temperature map on a linear scale from 0 keV (blue) to 11 keV (red). D. Eckert May 4, 2015

2Wherearethe“clusteroutskirts”?

Let us deﬁne, which radial range we consider as “cluster outskirts.” Readers not inter- ested in more details on the radial ranges can skip this section and just take note of our subjective choice: r500 < cluster outskirts < 3r200 , (1)

where r500 (defined below) used to be the observational limit for X-ray temperature measurements and the range up to 3r200 captures most of the interesting physics and chemistry before clearly entering the regime of the warm-hot intergalactic medium (WHIM, Fig. 1). This range also includes (i) the turn around radius, rturn =2rvir,from the spherical collapse model (e.g., Liddle & Lyth 2000), (ii)partoftheinfallregion where caustics in galaxy redshift space are observed, several Mpc (e.g., Diaferio 1999), (iii) much of the radial range where accretion shocks might beexpected,(1–3)rvir (e.g., Molnar et al. 2009), and (iv) the region where the two-halo term starts dominating over the one-halo term in the matter power spectrum, few Mpc (e.g.,Cooray&Sheth2002). Atheoreticalrecipethatcanbeusedtodefineacluster“border,” “boundary,” or at least a “characteristic” radius is the spherical collapse model (e.g., Amendola & Tsujikawa 2010). Based on this very idealistic model, a virial radius, rvir,separatingthevirialized cluster region from the outer “infall” region, can be obtained by requiring the mean total mass density of a cluster, ρtot ,tofulfill ⟨ ⟩ 3Mtot(

1 Some authors use the mean matter density of the Universe,ρ ¯m(z)=Ωm(z)ρc(z), instead of the critical density for their overdensity definition. A general entropy flattening in relaxed clusters?Auniversalentropyprofileforrelaxedclusters? 3

Walker et al. 2012

Figure 1. Left:Entropy profiles for the clusters shown in table 1, scaled by S(0.3r200) .Individualclustersarecolourcodedasshownintable1.Thesolid 1.1 Suzakublackdetected line shows the ther powerlaw ICMat relation large from radiiVoit et al. in (2005).∼10Right clusters:We plot S(r)/r (scaled to 0.3r200)toshowthedeviationfromapowerlawmore 1.1 (r/Br )2 clearly. The black line is the best fit line to the data outside 0.2r200 using a form S/S(0.3r200)=A(r/r200) e− 200 .Thebestfitusingthe Is thefunctional ICM form convectively of Cavaliere et al. unstable? (2011) (equation 1) is shown by the blue line. For each model the 2 σ variations calculated using Monte Carlo methods are shown by the dashed lines. The solid red lines show the range produced by density variations of 30 percent, which is the observed azimuthal density variation found near r200 in Eckert et al. (2012). D. Eckert May 4, 2015

model the entropy profiles well with best fit parameters AC = +0.23 +0.2 +0.8 1.02 0.08 , BC =1.8 0.2, CC =3.3 0.2,sothebestfitrelationis − − − 1.8 3.3(1 (r/R)) S/S(0.3r200)=1.02(r/R) e − (3)

Since the errors on each parameter are correlated, the errors on the best fits were obtained by using a Monte Carlo method with 10000 trials, and the 2 σ variations of the best fit models are shown by the dashed lines in Fig. 1 right. Black lines show equation 2 while the blue lines show equation 3. When performing the fitting the entropy profiles from each cluster were also weighted by the azimuthal coverage of the observations of each cluster (shown in Fig. 2), so that more weight was given to observations with larger, more representative azimuthal coverage. This reduces the possible bias of observations which were taken along narrow strips which may not be representative of the cluster as a whole. The solid red lines in Fig. 1 (right) show the effect of 30 percent density variations on the best fit entropy profile. This isthe Figure 2. Percentage azimuthal coverage as a function of radius for the level of azimuthal scatter in the gas density inferred from the az- observations used. imuthal scatter in the surface brightness of the clusters studied in Eckert et al. (2012) (where the observed surface brightness scatter was 70 percent around r200). We find that the majority of the ∼ In Fig. 1 (right) we plot S/r against r (scaling the pro- data lie within this range around the best fit profile, suggesting that most of the scatter around the best fit profile can be explained by files by S(0.3r200 )/0.3r200), which more clearly shows the de- the 30 percent azimuthal density variations found in Eckert et al. viation from a simple powerlaw above 0.5r200.Wefindthatthe ∼ (2012). The Virgo results are however inconsistent with the trend of profile is fitted well by the functional form S/S(0.3r200 )= 2 1.1 (r/Br200) the other clusters. This may be because the azimuthal scattermea- A(r/r200) e− for r ! 0.2r200 with best fitting pa- +0.3 +0.03 sured in Eckert et al. (2012) was found by dividing the clusters in rameters A =4.4 0.1 and B =1.0 0.06 ,sothat; − − their ROSAT sample into 12 sectors of opening angle 30 degrees, 2 1.1 (r/r200) whereas the Virgo strip is much narrower than this (its opening an- S/S(0.3r200 )=4.4(r/r200) e− (2) gle is 8degrees).Itisthereforepossiblethatthescattermeasured ∼ We also find the best fit to the scaled entropy profiles in the in Eckert et al. (2012) underestimates the level of scatter atscales range r ! 0.3r200 using the functional form of equation 1 from smaller than the sector size they used. Lapi et al. (2010) and Cavaliere et al. (2011), which is found to In Fig. 3 (black lines) we compare the scaled entropy profiles

c 0000 RAS, MNRAS 000,000–000 ! ROSAT density proﬁles

We analyzed a sample of 31 nearby NR profiles GADGET 10-3 ART clusters (0.04 < z < 0.2) ENZO ] -3 [cm -2 Emission-measure and deprojected 10-4 E(z) H density proﬁles for all clusters n

10-5 In average density proﬁles steepen 1.6 1.4 beyond R500 1.2 1 Ratio 0.8 Non-radiative simulations predict 0.6 0.4 too steep density slopes 0.2 0.4 0.6 0.8 1 1.2 r/r200 Eckert et al. 2012

D. Eckert May 4, 2015 Planck SZ results

Recently: Planck measures the SZ eﬀect beyond the virial radius Combined with ROSAT, we can reconstruct:

PSZ −5/3 kT = , K = PSZ nX −ray nX −ray

Assuming hydrostatic equilibrium we can also reconstruct mass proﬁles: Planck Collaboration V 2012 dP GM(< r) = −ρ dr r 2

D. Eckert May 4, 2015 Basic P and ngas proﬁles

10-1 102

-2 10 10 ] -3

[cm 1 /f(M) -2

-3 10 500 h(z)

P/P 10-1 gas n

-4 10 10-2

10-2 10-1 1 10-2 10-1 1 R/R500 R/R500 Eckert et al. 2012 Planck Collaboration V 2012

18 objects (6 CC, 12 NCC) are in common between the ROSAT and Planck samples

The average P and ngas proﬁles can also be combined (but caution about selection eﬀects)

D. Eckert May 4, 2015 Average entropy proﬁle

R200

6obj CC 12obj NCC Average CC

] Average NCC 2 Voit et al. 2005 103 [keV cm 2/3 h(z) -2/3 500 K M 102

10-1 1 R/R500 Eckert et al. 2013a CC clusters agree with the prediction from gravitational collapse (Voit et al. 2005) In NCC systems a deﬁcit with respect to the prediction is observed

D. Eckert May 4, 2015 Gas fraction proﬁles

We measure for the ﬁrst R200 time f at R , 0.25 gas 200 18obj parametric 18obj deprojection remarkable agreement Average parametric 0.2 Average deprojection between various methods WMAP7

fgas reaches the cosmic 0.15 gas value from WMAP7 at f 0.1 R200 Slight excess when 0.05

considering the stellar 0.5 1 1.5 2 R/R content (1-2%); predicted 500 by numerical simulations Eckert et al. 2013b

D. Eckert May 4, 2015 Gas fraction in CC/NCC systems

R200

6obj CC 12obj NCC Average CC 0.2 Average NCC

WMAP7

0.15 gas f

0.1

0.05 0.5 1 1.5 2

R/R500 Eckert et al. 2013b

For CC proﬁles fgas reaches the expected values (Ωb/Ωm − 15%)

For NCC proﬁles fgas exceeds the cosmic value!

D. Eckert May 4, 2015 X-ray signal biased towards high-density, cool regions:

hρ2i C 2 = > 1 hρi2

Gas clumping Properties of gas clumps and gas clumping factor in the ICM 3

Possible interpretation: gas clumping

The accretion ﬂow on galaxy clusters is clumpy and asymmetric relaxed post merger merging

relaxed post merger merging

Vazza, DE et al. 2012 1.00e-18 1.48e-15 7.41e-15 3.11e-14 1.26e-13 5.00e-13

Figure 2. Top panels: X-ray flux in the [0.5-2] keV (in [erg/(s cm2)]) of three simulated clusters of our sample at z=0 (E15B-relax, E1-post merger and · D. Eckert May 4,E3B-merging). 2015 Bottom panels: X-ray flux of clumps identified by our procedure (also highlighted with white contours). Theinnerandouterprojectedarea excluded from our analysis have been shadowed. The area shownwithineachpanelis 3 3R200 for each object. ∼ ×

DM particles and 25 kpc/h in most of the cluster volume in- mal energy inside the virial radius at z =0,sincethisquantitypa- ∼ side the ”AMR region” (i.e. 2 3 R200 from the cluster centre, rameter provides an indication of the dynamical activity of acluster ∼ − see Vazza et al. 2010; Vazza 2011a; Vazza et al. 2011a for further (e.g. Tormen et al. 1997; Vazza et al. 2006). Using this proxy,we details). defined as ”merging” systems those objects that present an energy ratio > 0.4,butdidnotexperiencedamajormergerintheirpast We assumed a concordance ΛCDM cosmology, with Ω0 = (e.g. they show evidence of ongoing accretion with a companion 1.0, ΩB =0.0441, ΩDM =0.2139, ΩΛ =0.742,Hubbleparame- ter h =0.72 and a normalization for the primordial density power of comparable size, but the cores of the two systems did not en- counter yet). The remaining systems were classified as ”relaxed”. spectrum of σ8 =0.8.Mostoftherunswepresentinthiswork (Sec.3.1-3.2) neglect radiative cooling, star formation and AGN According to the above classification scheme, our sample presents feedback processes. In Sec.3.3, however, we discuss additional runs 4relaxedobjects,6mergingobjectsand10post-mergerobjects. where the following non-gravitational processes are modelled: ra- Based on our further analysis of this sample, this classifica- diative cooling, thermal feedback from AGN, and pressure feed- tion actually mirrors a different level of dynamical activity in the back from cosmic ray particles (CR) injected at cosmologicalshock subgroups, i.e. relaxed systems on average host weaker shocks waves. (Vazza et al. 2010), they are characterized by a lowest turbulent For consistency with our previous analysis on the same sam- to thermal energy ratio (Vazza et al. 2011a), and they are char- ple of galaxy clusters (Vazza et al. 2010, 2011a,c), we divided our acterized by the smallest amount of azimuthal scatter in the gas sample in dynamical classes based on the total matter accretion properties (Vazza et al. 2011c; Eckert et al. 2012). In Vazza et al. history of each halo for z ! 1.0.First,wemonitoredthetime (2011c) the same sample was also divided based on the analysisof evolution of the DM+gas mass for every object inside the ”AMR the power ratios from the multi-pole decomposition of the X-ray region” in the range 0.0 ! z ! 1.0.Consideringatimelapseof surface brightness images (P3/P0), and the centroid shift (w), as ∆t =1Gyr,”majormerger”eventsaredetectedastotalmatterac- described by Böhringer et al. (2010). These morphological param- cretion episode where M(t + ∆t)/M (t) 1 > 1/3.Thesystems eters of projected X-ray emission maps were measured inside the − with a lower accretion rate were further divided by measuringthe innermost projected 1Mpc2.Thisleadstodecomposeoursam- ratio between the total kinetic energy of gas motions and the ther- ple into 9 ”non-cool-core-like” (NCC) systems, and 11 ”cool-core- Gas clumping Properties of gas clumps and gas clumping factor in the ICM 3

Possible interpretation: gas clumping

The accretion ﬂow on galaxy clusters is clumpy and asymmetric relaxed post merger merging

X-ray signal biased towards high-density, cool regions:

hρ2i C 2 = > 1 hρi2

relaxed post merger merging

Vazza, DE et al. 2012 1.00e-18 1.48e-15 7.41e-15 3.11e-14 1.26e-13 5.00e-13

DM particles and 25 kpc/h in most of the cluster volume in- mal energy inside the virial radius at z =0,sincethisquantitypa- ∼ side the ”AMR region” (i.e. 2 3 R200 from the cluster centre, rameter provides an indication of the dynamical activity of acluster ∼ − see Vazza et al. 2010; Vazza 2011a; Vazza et al. 2011a for further (e.g. Tormen et al. 1997; Vazza et al. 2006). Using this proxy,we details). defined as ”merging” systems those objects that present an energy ratio > 0.4,butdidnotexperiencedamajormergerintheirpast We assumed a concordance ΛCDM cosmology, with Ω0 = (e.g. they show evidence of ongoing accretion with a companion 1.0, ΩB =0.0441, ΩDM =0.2139, ΩΛ =0.742,Hubbleparame- ter h =0.72 and a normalization for the primordial density power of comparable size, but the cores of the two systems did not en- counter yet). The remaining systems were classified as ”relaxed”. spectrum of σ8 =0.8.Mostoftherunswepresentinthiswork (Sec.3.1-3.2) neglect radiative cooling, star formation and AGN According to the above classification scheme, our sample presents feedback processes. In Sec.3.3, however, we discuss additional runs 4relaxedobjects,6mergingobjectsand10post-mergerobjects. where the following non-gravitational processes are modelled: ra- Based on our further analysis of this sample, this classifica- diative cooling, thermal feedback from AGN, and pressure feed- tion actually mirrors a different level of dynamical activity in the back from cosmic ray particles (CR) injected at cosmologicalshock subgroups, i.e. relaxed systems on average host weaker shocks waves. (Vazza et al. 2010), they are characterized by a lowest turbulent For consistency with our previous analysis on the same sam- to thermal energy ratio (Vazza et al. 2011a), and they are char- ple of galaxy clusters (Vazza et al. 2010, 2011a,c), we divided our acterized by the smallest amount of azimuthal scatter in the gas sample in dynamical classes based on the total matter accretion properties (Vazza et al. 2011c; Eckert et al. 2012). In Vazza et al. history of each halo for z ! 1.0.First,wemonitoredthetime (2011c) the same sample was also divided based on the analysisof evolution of the DM+gas mass for every object inside the ”AMR the power ratios from the multi-pole decomposition of the X-ray region” in the range 0.0 ! z ! 1.0.Consideringatimelapseof surface brightness images (P3/P0), and the centroid shift (w), as ∆t =1Gyr,”majormerger”eventsaredetectedastotalmatterac- described by Böhringer et al. (2010). These morphological param- cretion episode where M(t + ∆t)/M (t) 1 > 1/3.Thesystems eters of projected X-ray emission maps were measured inside the − with a lower accretion rate were further divided by measuringthe innermost projected 1Mpc2.Thisleadstodecomposeoursam- ratio between the total kinetic energy of gas motions and the ther- ple into 9 ”non-cool-core-like” (NCC) systems, and 11 ”cool-core- Hydrodynamical simulations predict too many substructures in the outskirts Including AGN + SN feedback improves the match

Gas clumping factor

Azimuthal median is robust against inhomogeneities

Azimuthal mean

1 Azimuthal median

10-1 X S 10-2

10-3

10-4

10-1 1 R/R200 Eckert et al. 2015

D. Eckert May 4, 2015 Gas clumping factor

ROSAT/PSPC ENZO NR GADGET NR GADGET CSF+AGN

R200 2

Data V13 1.8 R13 NR R13 CSF+AGN 1.6 R13 Residual C 1.4

1.2

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

R/R500 Eckert et al. 2015

Hydrodynamical simulations predict too many substructures in the outskirts Including AGN + SN feedback improves the match

D. Eckert May 4, 2015 Accreting substructures in A2142

We obtained 250 ks XMM observations of A2142 and Hydra A in AO-11 to look for accreting substructures

27.6

27.5

27.4

27.3

27.2 Declination 27.1

27.0

26.9

26.8 240.1 240.0 239.9 239.8 239.7 239.6 239.5 239.4 239.3 239.2 239.1 Right ascension Eckert et al. 2014

D. Eckert May 4, 2015 Accreting substructures in A2142

We obtained 250 ks XMM observations of A2142 and Hydra A in AO-11 to look for accreting substructures

Eckert et al. 2014

D. Eckert May 4, 2015 Tip of the substructure

27.50

27.48 G1 27.46

27.44 G2

27.42 Declination

27.40 G3 G4

27.38 G5

27.36 239.84 239.82 239.80 239.78 239.76 239.74 239.72 239.70 239.68 Right ascension

The tip of the X-ray substructure is associated with an infalling galaxy group. The bulk of the gas is lagging behind

D. Eckert May 4, 2015 Spectral analysis

Sector 2 1 0.01 0.1 keV 1 3 10 normalized counts s 4 10

0.51 2 5 10 Energy (keV) The gas is signiﬁcantly cooler (kT ∼ 1.4 keV) than the ambient ICM (∼ 7 keV). Temperature typical of a galaxy group with mass of 13 a few 10 M . → Disruption of an infalling group within the DM halo of the main structure

D. Eckert May 4, 2015 Assuming pressure equilibrium at the tip we can estimate the infall velocity: 2 PICM + ρICMv ≈ Pgroup

We ﬁnd that Pgroup > PICM, such that we obtain v ∼ 1,200 km s−1 for the infall velocity ⇒ the feature has been surviving in the cluster environment for at least 600 Myr

For a typical group Pram should exceed Pth throughout most of the volume, such that > 90% of the gas mass has been already stripped

Ram-pressure stripping properties

This by far the largest stripped structure seen so far: Projected distance > 800 kpc compared to 150 kpc for M86 12 10 Gas mass ∼ 2 × 10 M compared to ∼ 10 M for M86

D. Eckert May 4, 2015 For a typical group Pram should exceed Pth throughout most of the volume, such that > 90% of the gas mass has been already stripped

Ram-pressure stripping properties

This by far the largest stripped structure seen so far: Projected distance > 800 kpc compared to 150 kpc for M86 12 10 Gas mass ∼ 2 × 10 M compared to ∼ 10 M for M86 Assuming pressure equilibrium at the tip we can estimate the infall velocity: 2 PICM + ρICMv ≈ Pgroup

We ﬁnd that Pgroup > PICM, such that we obtain v ∼ 1,200 km s−1 for the infall velocity ⇒ the feature has been surviving in the cluster environment for at least 600 Myr

D. Eckert May 4, 2015 Ram-pressure stripping properties

We ﬁnd that Pgroup > PICM, such that we obtain v ∼ 1,200 km s−1 for the infall velocity ⇒ the feature has been surviving in the cluster environment for at least 600 Myr

For a typical group Pram should exceed Pth throughout most of the volume, such that > 90% of the gas mass has been already stripped

D. Eckert May 4, 2015 The thermal conduction timescale in a plasma is

2 2 ` 3ne ` kB tcond ∼ = Dcond 2κ In an unmagnetized plasma −5 κ = κSpitzer; for ne ∼ 5 × 10 cm−3 and kT ∼ 5 keV we ﬁnd tcond ∼ 1.4 Myr Thermal conduction in the ICM is inhibited by a factor & 400!

pared with f = 1model,thedensityfluctuationsincreasebya factor of 0.3 on large scales, while small perturbationshavesimi- lar power. The absence of a dramatic decline is mainly due to the fact that on small scales the sound crossing time becomes greater than the conduction time (e.g. Fig. 8), hence the tiny bubblesdo not have time to find a new pressure equilibrium. Besides global diffusion, strong conduction can thus promote minor stirring motions on small scales, preventing an abrupt decay of A(k)δ. In this run, the spectrum slope in the inertial regime is steep, A(k) k 2/3,significantlydifferent from the no-conduction run. δ ∝ − Radial profiles and SBx maps (Fig. 4, bottom) are very similar to the f = 1model,retainingtheirinitialsphericalmorphology. The Pt number is roughly 10 at the injection scale. Albeit turbulent regeneration starts to be more effective on large scales, the key Pt threshold appears to be an order of magnitude higher, as shown by the next model. We suppress further the conductive flux by f = 2 10− ,avalueadvocatedbyseveralplasmaphysicstheories (e.g. Rechester & Rosenbluth 1978; Chandran & Cowley 1998). The Prandtl number is 100 at the injection scale: turbulence can now restore part of the perturbations, though only near L (the normalization rises again to 6percent).Thismarkeddiscrep- ancy between large and small∼ scales induces a remarkably steep 4/5 2.5 slope, A(k)δ k− (E(k) k− ), which should emerge in ob- ∝ ∝ 2 served data in a clear way, if f 10− is the conductive regime of the ICM. The δρ/ρ map (Fig.∼ 3, third panel) visualizes well the regeneration of turbulent eddies on large scales, while the small-scale flow remains considerably smooth, as corroborated Thermal conduction by the SBx map (Fig. 4, third row). Since this model shows a clear cutoff,itrepresentsthecleanestcasetoretrievethekey threshold for the suppression of density perturbations, which we findpared to with be Pft = 1model,thedensityfluctuationsincreasebya100. This is not a strict demarcation line, but ∼ ratherfactor aof transition 0.3 on large layer. scales, while small perturbationshavesimi- 3 Thermal conduction “washes out" lar power.Only when The absenceconduction of a is dramatic substantially decline suppressed, is mainly duef = to10 the− (thefact typicallythat on small lowest scales suppression the sound factor crossing adopted time becomes in theories), greater the inhomogeneities turbulentthan the conduction cascade is time significantly (e.g. Fig. restored, 8), hence generating the tiny bubble thesamesdo peaknot have and time density to find spectrum a new pressure down to equilibrium.L/2. Since Besides thermal glob dif-al fusiondiffusion, is too strong week, conduction Kelvin-Helmholtz can thus∼ rolls promote and Rayleigh-Ta minor stirringylor The thermal conduction timescale instabilitiesmotions on cansmall develop scales, again preventing over a an large abrupt range, decay defining of A(kthe)δ. entireIn this flow run, dynamics the spectrum (Fig. slope 3) and in perturbing the inertial the regime X-ray is surfac steep,e brightnessA(k) k 2 (Fig./3,significantlydi 4, second row).fferent Turbulent from the di no-conductionffusion is able run. to in a plasma is δ ∝ − eRadialfficiently profiles mix the and entropy SBx maps profile, (Fig. again 4, bottom) lowering are/increasing very similar the centralto the f density= 1model,retainingtheirinitialsphericalmorphology./temperature (the discrepancy between Te and Ti < 2 2 isThe nowPt number1percent;§4.1).Conductioncana is roughly 10 at the injectionff scale.ect only Albeit the turbu-scales ` 3ne ` kB smallerlent regeneration∼ than 100 kpc, starts creating to be more a gentle effective exponential on large decreas scales,ein the tcond ∼ = thekey logarithmicPt thresholdA appears(k)δ.Thesuppressionof to be an order of magnitudeδ reaches a higher, factor ofas Dcond 2κ 2near30kpc.Noticehowconductionstilldominatesthedif-shown by the next model. fusivity,We overcoming suppress further (numerical) the viscosity.conductive When flux turbule by fnt re-= 2 generation10− ,avalueadvocatedbyseveralplasmaphysicstheories is efficient, it is not trivial to define an exact cutoff. In an unmagnetized plasma Nevertheless,(e.g. Rechester the & threshold RosenbluthPt 1978;100 Chandran (l 100 kpc) & Cowley appears 1998). a ro- bustThe criterium:Prandtl number at that is scale 100 weat the∼ see injection the beginning∼ scale: of turbulence a substantialcan −5 1/2 κ = κSpitzer; for ne ∼ 5 × 10 decaynow restore of the density part of spectrumthe perturbations, (changing though slope to onlyk− near). L (the −3 normalization rises again to 6percent).Thismarkeddiscrep- cm and kT ∼ 5 keV we find ancy between large and small∼ scales induces a remarkably steep 3.2. Mild turbulence:4/5 M 0.5 2.5 slope, A(k)δ k− (E(k∼) k− ), which should emerge in ob- ∝ ∝ 2 tcond ∼ 1.4 Myr Weserved now data increase in a clear the way,level if off turbulent10− is motions the conductive by a factor regime of 1∼ two,of theM ICM.0.5( Theσvδρ/750ρ map km (Fig. s− ). 3, Turbulent third panel) energy visualizes is thus well14 percentthe regeneration of∼ the thermal of∼ turbulent energy, eddiesstill within on large the range scales, retrie whileved∼the by ICMsmall-scale observations flow remains and cosmological considerably simulations. smooth, as The corrobora character-ted isticby the eddy SB turnoverx map (Fig. time 4, is thirdt row).0.8Gyr. Since this model shows a eddy ∼ clearFigure cutoff 5,itrepresentsthecleanestcasetoretrievethekey shows that the overall behaviour of A(k)δ is similar tothreshold the previous for the set suppression of models, of with density differences perturbations, laying inwh theich de- we find to be Pt 100. This is not= a strict demarcation line, but Fig. 3. Mid-plane cuts of δρ/ρ for theGaspari models & with ChurazovM 0.25. 2013 From tails. The purely∼ turbulent case ( f 0) forms the usual injection top to bottom: f = 0, 10 3, 10 2, 10 1 (the latter very similar∼ to f = 1 peak,rather with a transition maximum layer. at 12 percent (Table 1), i.e. two times − − − Only when conduction∼ is substantially suppressed, f = 10 3 D. Eckert Mayrun). 4, The 2015 color coding is blue white red: -40% 0% 40%. − page 8 of 17 → → → → (the typically lowest suppression factor adopted in theories), the turbulent cascade is significantly restored, generating thesame peak and density spectrum down to L/2. Since thermal diffusion is too week, Kelvin-Helmholtz∼ rolls and Rayleigh-Taylor instabilities can develop again over a large range, defining the entire flow dynamics (Fig. 3) and perturbing the X-ray surface brightness (Fig. 4, second row). Turbulent diffusion is able to efficiently mix the entropy profile, again lowering/increasing the central density/temperature (the discrepancy between Te and Ti is now < 1percent;§4.1).Conductioncanaffect only the scales smaller∼ than 100 kpc, creating a gentle exponential decreasein the logarithmic A(k)δ.Thesuppressionofδ reaches a factor of 2near30kpc.Noticehowconductionstilldominatesthedif- fusivity, overcoming (numerical) viscosity. When turbulent regeneration is efficient, it is not trivial to define an exact cutoff. Nevertheless, the threshold Pt 100 (l 100 kpc) appears a robust criterium: at that scale we∼ see the beginning∼ of a substantial 1/2 decay of the density spectrum (changing slope to k− ).

3.2. Mild turbulence: M 0.5 ∼ We now increase the level of turbulent motions by a factor of 1 two, M 0.5(σv 750 km s− ). Turbulent energy is thus 14 percent of∼ the thermal∼ energy, still within the range retrieved∼ by ICM observations and cosmological simulations. The characteristic eddy turnover time is t 0.8Gyr. eddy ∼ Figure 5 shows that the overall behaviour of A(k)δ is similar to the previous set of models, with differences laying in the de- Fig. 3. Mid-plane cuts of δρ/ρ for the models with M 0.25. From tails. The purely turbulent case ( f = 0) forms the usual injection 3 2 1 ∼ peak, with maximum at 12 percent (Table 1), i.e. two times top to bottom: f = 0, 10− , 10− , 10− (the latter very similar to f = 1 ∼ run). The color coding is blue white red: -40% 0% 40%. page 8 of 17 → → → → pared with f = 1model,thedensityfluctuationsincreasebya factor of 0.3 on large scales, while small perturbationshavesimi- lar power. The absence of a dramatic decline is mainly due to the fact that on small scales the sound crossing time becomes greater than the conduction time (e.g. Fig. 8), hence the tiny bubblesdo not have time to find a new pressure equilibrium. Besides global diffusion, strong conduction can thus promote minor stirring motions on small scales, preventing an abrupt decay of A(k)δ. In this run, the spectrum slope in the inertial regime is steep, A(k) k 2/3,significantlydifferent from the no-conduction run. δ ∝ − Radial profiles and SBx maps (Fig. 4, bottom) are very similar to the f = 1model,retainingtheirinitialsphericalmorphology. The Pt number is roughly 10 at the injection scale. Albeit turbulent regeneration starts to be more effective on large scales, the key Pt threshold appears to be an order of magnitude higher, as shown by the next model. We suppress further the conductive flux by f = 2 10− ,avalueadvocatedbyseveralplasmaphysicstheories (e.g. Rechester & Rosenbluth 1978; Chandran & Cowley 1998). The Prandtl number is 100 at the injection scale: turbulence can now restore part of the perturbations, though only near L (the normalization rises again to 6percent).Thismarkeddiscrep- ancy between large and small∼ scales induces a remarkably steep 4/5 2.5 slope, A(k)δ k− (E(k) k− ), which should emerge in ob- ∝ ∝ 2 served data in a clear way, if f 10− is the conductive regime of the ICM. The δρ/ρ map (Fig.∼ 3, third panel) visualizes well the regeneration of turbulent eddies on large scales, while the small-scale flow remains considerably smooth, as corroborated Thermal conduction by the SBx map (Fig. 4, third row). Since this model shows a clear cutoff,itrepresentsthecleanestcasetoretrievethekey threshold for the suppression of density perturbations, which we findpared to with be Pft = 1model,thedensityfluctuationsincreasebya100. This is not a strict demarcation line, but ∼ ratherfactor aof transition 0.3 on large layer. scales, while small perturbationshavesimi- 3 Thermal conduction “washes out" lar power.Only when The absenceconduction of a is dramatic substantially decline suppressed, is mainly duef = to10 the− (thefact typicallythat on small lowest scales suppression the sound factor crossing adopted time becomes in theories), greater the inhomogeneities turbulentthan the conduction cascade is time significantly (e.g. Fig. restored, 8), hence generating the tiny bubble thesamesdo peaknot have and time density to find spectrum a new pressure down to equilibrium.L/2. Since Besides thermal glob dif-al fusiondiffusion, is too strong week, conduction Kelvin-Helmholtz can thus∼ rolls promote and Rayleigh-Ta minor stirringylor The thermal conduction timescale instabilitiesmotions on cansmall develop scales, again preventing over a an large abrupt range, decay defining of A(kthe)δ. entireIn this flow run, dynamics the spectrum (Fig. slope 3) and in perturbing the inertial the regime X-ray is surfac steep,e brightnessA(k) k 2 (Fig./3,significantlydi 4, second row).fferent Turbulent from the di no-conductionffusion is able run. to in a plasma is δ ∝ − eRadialfficiently profiles mix the and entropy SBx maps profile, (Fig. again 4, bottom) lowering are/increasing very similar the centralto the f density= 1model,retainingtheirinitialsphericalmorphology./temperature (the discrepancy between Te and Ti < 2 2 isThe nowPt number1percent;§4.1).Conductioncana is roughly 10 at the injectionff scale.ect only Albeit the turbu-scales ` 3ne ` kB smallerlent regeneration∼ than 100 kpc, starts creating to be more a gentle effective exponential on large decreas scales,ein the tcond ∼ = thekey logarithmicPt thresholdA appears(k)δ.Thesuppressionof to be an order of magnitudeδ reaches a higher, factor ofas Dcond 2κ 2near30kpc.Noticehowconductionstilldominatesthedif-shown by the next model. fusivity,We overcoming suppress further (numerical) the viscosity.conductive When flux turbule by fnt re-= 2 generation10− ,avalueadvocatedbyseveralplasmaphysicstheories is efficient, it is not trivial to define an exact cutoff. In an unmagnetized plasma Nevertheless,(e.g. Rechester the & threshold RosenbluthPt 1978;100 Chandran (l 100 kpc) & Cowley appears 1998). a ro- bustThe criterium:Prandtl number at that is scale 100 weat the∼ see injection the beginning∼ scale: of turbulence a substantialcan −5 1/2 κ = κSpitzer; for ne ∼ 5 × 10 decaynow restore of the density part of spectrumthe perturbations, (changing though slope to onlyk− near). L (the −3 normalization rises again to 6percent).Thismarkeddiscrep- cm and kT ∼ 5 keV we find ancy between large and small∼ scales induces a remarkably steep 3.2. Mild turbulence:4/5 M 0.5 2.5 slope, A(k)δ k− (E(k∼) k− ), which should emerge in ob- ∝ ∝ 2 tcond ∼ 1.4 Myr Weserved now data increase in a clear the way,level if off turbulent10− is motions the conductive by a factor regime of 1∼ two,of theM ICM.0.5( Theσvδρ/750ρ map km (Fig. s− ). 3, Turbulent third panel) energy visualizes is thus well14 percentthe regeneration of∼ the thermal of∼ turbulent energy, eddiesstill within on large the range scales, retrie whileved∼the by Thermal conduction in the ICM is ICMsmall-scale observations flow remains and cosmological considerably simulations. smooth, as The corrobora character-ted isticby the eddy SB turnoverx map (Fig. time 4, is thirdteddy row).0.8Gyr. Since this model shows a ff ∼ inhibited by a factor 400! clearFigure cuto 5,itrepresentsthecleanestcasetoretrievethekey shows that the overall behaviour of A(k)δ is similar & tothreshold the previous for the set suppression of models, of with density differences perturbations, laying inwh theich de- we find to be Pt 100. This is not= a strict demarcation line, but Fig. 3. Mid-plane cuts of δρ/ρ for theGaspari models & with ChurazovM 0.25. 2013 From tails. The purely∼ turbulent case ( f 0) forms the usual injection top to bottom: f = 0, 10 3, 10 2, 10 1 (the latter very similar∼ to f = 1 peak,rather with a transition maximum layer. at 12 percent (Table 1), i.e. two times − − − Only when conduction∼ is substantially suppressed, f = 10 3 D. Eckert Mayrun). 4, The 2015 color coding is blue white red: -40% 0% 40%. − page 8 of 17 → → → → (the typically lowest suppression factor adopted in theories), the turbulent cascade is significantly restored, generating thesame peak and density spectrum down to L/2. Since thermal diffusion is too week, Kelvin-Helmholtz∼ rolls and Rayleigh-Taylor instabilities can develop again over a large range, defining the entire flow dynamics (Fig. 3) and perturbing the X-ray surface brightness (Fig. 4, second row). Turbulent diffusion is able to efficiently mix the entropy profile, again lowering/increasing the central density/temperature (the discrepancy between Te and Ti is now < 1percent;§4.1).Conductioncanaffect only the scales smaller∼ than 100 kpc, creating a gentle exponential decreasein the logarithmic A(k)δ.Thesuppressionofδ reaches a factor of 2near30kpc.Noticehowconductionstilldominatesthedif- fusivity, overcoming (numerical) viscosity. When turbulent regeneration is efficient, it is not trivial to define an exact cutoff. Nevertheless, the threshold Pt 100 (l 100 kpc) appears a robust criterium: at that scale we∼ see the beginning∼ of a substantial 1/2 decay of the density spectrum (changing slope to k− ).

Another galaxy group 1.1 Mpc South of the cluster core

De Grandi, DE et al. in prep.

800 kpc tail bent by the motion of the group

D. Eckert May 4, 2015 Abell 2744 (z = 0.306): the Pandora cluster

Abell 2744 was observed by HST for the Frontier Fields initiative (Jauzac et al. 2015)

Jauzac et al. 2015 We detected ∼ 50 lensed galaxies in this cluster, corresponding mass model known at 1% precision! D. Eckert May 4, 2015 XMM-Newton observation of Abell 2744

We recently obtained a deep (110ks) observation of this cluster with XMM-Newton (PI: J.-P. Kneib)

Eckert et al. submitted We discovered 5 regions of extended X-ray emission radially connected to the cluster D. Eckert May 4, 2015 Hot gas ﬁlaments in Abell 2744

Signiﬁcant extended emission detected in the direction of the ﬁlaments out to ∼ 4 Mpc

Eckert et al. submitted

D. Eckert May 4, 2015 Hot gas ﬁlaments in Abell 2744

The ﬁlamentary structures correspond with overdensities of cluster galaxies...

Eckert et al. submitted

D. Eckert May 4, 2015 Hot gas ﬁlaments in Abell 2744

The ﬁlamentary structures correspond with overdensities of cluster galaxies... and DM!

150’’ E

Eckert et al. submitted

D. Eckert May 4, 2015 Nature of the ﬁlaments

Spectral analysis reveals thermal gas with T ∼ 1 keV

Eckert et al. submitted We are observing diﬀuse hot gas originating from the LSS and heated up by the gravitational pull of A2744 D. Eckert May 4, 2015 Dominique Eckert Part B2 X-COP

Section b. Methodology b.1. Available Data: The XMM-Newton Cluster Outskirts VLP In December 2013 I was awarded a Very Large Program (VLP) on ESA's cornerstone X- ray mission XMM-Newton to map the outer regions of a dozen of clusters with unprecedented sensitivity. This observing program, in combination with a dedicated analysis of the Planck public data, will enable a large fraction of the science goals of X- COP. X-COP is based on the data from two major ESA missions: XMM-Newton and Planck. XMM-Newton (Jansen et al. 2001) is an ESA mission launched in 1999. It carries three Wolter-type grazing-incidence telescopes which are the largest ever flown on an X-ray satellite, for a combined effective area of 3,000 cm2 at 1 keV and an effective area of 13 arcsec HEW. In AO-13 I was awarded a VLP (ID: 074441) for a total observing time of 1207 ks (335 hours) on this major observatory. This is the largest program awarded this year. This TheVLP XMMfollows a pilot Cluster study based on Outskirts two clusters (282 VLPks, ID: 069444 and 072524). In the pilot study (A2142 and A780) we demonstrated that XMM-Newton is capable of detecting diffuse X-ray emission out to the virial radius provided that the right observing strategy is used. In total, this project will benefit from a total allotted time of nearly 1.5 Ms on XMM-Newton. This demonstrates that the science developed in X-COP was highlyXMM prioritized AO-13 by the VLP, various total XMM-Newton 1.2 Ms:selection Construct panels. a sample of 13 clusters Inat total, 0.04 X-COP< z will< provide0.1with a detailed high-S/N X-ray mappingPlanck of the entiredetection volume of and13 clusters XMM in the redshift range 0.04-0.1 at unprecedented depth. The list of clusters is provided in the Table below. mapping of the entire azimuth

14 Cluster Redshift Mass [10 M] Planck S/N A2319 0.0557 5.83 30.8 A3266** 0.0589 4.56 27.0 A2142* 0.090 8.15 21.3 A2255 0.0809 3.74 19.4 A2029 0.0766 7.27 19.3 A3158 0.059 3.65 17.2 A85 0.0555 5.32 16.9 A1795 0.0622 5.53 15.0 A644 0.0704 3.88 13.9 RXC J1825 0.065 2.62 13.4 A1644 0.0473 2.93 13.2 ZwCl 1215 0.0766 3.59 12.8 A780* 0.0538 1.89 - Clusters identified by * were part of the pilot program. A similar program for A3266** is already publicly available. With the exception of Hydra A/A780, whichD. Eckert was selectedMay because 4, 2015 of the presence of several accreting substructures in its outskirts, the sample was selected on the basis on the signal-to-noise ratio in the Planck sample (Planck Collaboration XXIX, 2013). Therefore, X-COP is a carefully-selected SZ sample. This is a very important property to pursue our objectives, since the SZ selection is renown for its purity; this will . allow us to extract for the first time meaningful results on the cluster population beyond R500. Moreover, in addition to the outstanding quality of the available X-ray data, since these systems are the brightest in the Planck catalog we will get high-precision information also from the SZ side. The objects targeted in this analysis are nearby, so they are well-resolved by Planck in spite of its large beam (7 arcmin). The X-COP sample has been designed to reach the best possible sensitivity both in X-rays and SZ. The data for the VLP will start to be collected in the course of 2014 and the data-taking will be completed in mid- 2015.

10 Summary

Cluster outskirts are the region where structure formation occurs at the present epoch We measure for the ﬁrst time thermodynamic quantities out to the virial radius in a substantial cluster sample Evidence for gas clumping and/or breakdown of hydrostatic equilibrium in cluster outskirts

fgas reaches the cosmic value at R200, providing evidence that all the primordial gas is collapsed into clusters We discovered stripped infalling galaxy groups in A2142 and Hydra A We detected ﬁlaments of hot gas in the z = 0.3 cluster A2744, evidence for the WHIM? More to come thanks to an accepted VLP on XMM

D. Eckert May 4, 2015 Backup Slides Validation of the method

We collected available X-ray T proﬁles and compared with our method Combining SZ pressure with X-ray density we are able to reproduce the observed X-ray temperatures within < 10% Eckert et al. 2013a

D. Eckert May 4, 2015 Our temperature determination at R200 is very reliable

Average temperature proﬁle

R200

4.5 18obj parametric 18obj deprojection Average parametric 4 Average deprojection

3.5 [keV] -2/3 3 h(z) 2.5 -2/3 500

kT M 2

1.5

0.5 1 1.5 2 R/R 500Eckert et al. 2013a Average temperature from the mean profiles agrees very well with the average of the 18 individual objects Two different deprojection methods (parametric fitting, geometrical deprojection) also yield similar results

D. Eckert May 4, 2015 Average temperature proﬁle

R200

4.5 18obj parametric 18obj deprojection Average parametric 4 Average deprojection

3.5 [keV] -2/3 3 h(z) 2.5 -2/3 500

kT M 2

1.5

Our temperature determination at R200 is very reliable

D. Eckert May 4, 2015 When correcting for gas depletion, the total entropy agrees perfectly with the self-similar prediction out to Rvir

Correcting for gas depletion

Following Pratt et al. (2010) we rescale the entropy proﬁles by the gas fraction to compensate for gas motions

R200

6obj CC 12obj NCC Average CC Average NCC Voit et al. 2005 2/3 1 h(z) -2/3 b f 2/3 gas f 500 K/K 10-1

10-1 1 R/R500 Eckert et al. subm I

D. Eckert May 4, 2015 Correcting for gas depletion

Following Pratt et al. (2010) we rescale the entropy proﬁles by the gas fraction to compensate for gas motions

R200

6obj CC 12obj NCC Average CC Average NCC Voit et al. 2005 2/3 1 h(z) -2/3 b f 2/3 gas f 500 K/K 10-1

10-1 1 R/R500 Eckert et al. subm I When correcting for gas depletion, the total entropy agrees perfectly with the self-similar prediction out to Rvir

D. Eckert May 4, 2015 Our results are at odds with this interpretation

A general entropy ﬂattening in relaxed clusters?

Auniversalentropyproﬁleforrelaxedclusters? 3

Suzaku detected the ICM at large radii in ∼10 clusters Is the ICM convectively unstable? Challenging for structure formation models Walker et al. (2012) fix the normalization of the self-similar profile to match the observations at 0.3R200 instead of using the self-similar normalization K (Pratt et al. Walker et al. 2012 500 Figure 1. Left:Entropy profiles for the clusters shown in table 1, scaled by S(0.3r200) .Individualclustersarecolourcodedasshownintable1.Thesolid 1.1 black line shows the r powerlaw relation from Voit et al. (2005). Right:We plot S(r)/r (scaled to 0.3r200)toshowthedeviationfromapowerlawmore 2010) 1.1 (r/Br )2 clearly. The black line is the best fit line to the data outside 0.2r200 using a form S/S(0.3r200)=A(r/r200) e− 200 .Thebestfitusingthe functional form of Cavaliere et al. (2011) (equation 1) is shown by the blue line. For each model the 2 σ variations calculated using Monte Carlo methods are shown by the dashed lines. The solid red lines show the range produced by density variations of 30 percent, which is the observed azimuthal density variation found near r200 in Eckert et al. (2012).

D. Eckert May 4, 2015 model the entropy profiles well with best fit parameters AC = +0.23 +0.2 +0.8 1.02 0.08 , BC =1.8 0.2, CC =3.3 0.2,sothebestfitrelationis − − − 1.8 3.3(1 (r/R)) S/S(0.3r200)=1.02(r/R) e − (3)

c 0000 RAS, MNRAS 000,000–000 ! A general entropy ﬂattening in relaxed clusters?

Auniversalentropyproﬁleforrelaxedclusters? 3

Suzaku detected the ICM at large radii in ∼10 clusters Is the ICM convectively unstable? Challenging for structure formation models Walker et al. (2012) fix the normalization of the self-similar profile to match the observations at 0.3R200 instead of using the self-similar normalization K (Pratt et al. Walker et al. 2012 500 Figure 1. Left:Entropy profiles for the clusters shown in table 1, scaled by S(0.3r200) .Individualclustersarecolourcodedasshownintable1.Thesolid 1.1 black line shows the r powerlaw relation from Voit et al. (2005). Right:We plot S(r)/r (scaled to 0.3r200)toshowthedeviationfromapowerlawmore 2010) 1.1 (r/Br )2 clearly. The black line is the best fit line to the data outside 0.2r200 using a form S/S(0.3r200)=A(r/r200) e− 200 .Thebestfitusingthe functional form of Cavaliere et al. (2011) (equation 1) is shown by the blue line. For each model the 2 σ variations calculated using Monte Carlo methods are Our results are at odds with thisshown interpretation by the dashed lines. The solid red lines show the range produced by density variations of 30 percent, which is the observed azimuthal density variation found near r200 in Eckert et al. (2012).

c 0000 RAS, MNRAS 000,000–000 !