Lectures for graduate students in Astrophysics on high redshift galaxy clusters. Winter School Francesco Lucchin.

1. Multi-λ observations & Surveys
of Galaxy Clusters
Joana S. Santos
INAF - Arcetri
Francesco Lucchin School
INAF /Teramo
9-13 December 2014
The Bullet Cluster
credit: Chandra X-ray Observatory

2. OUTLINE OFTHE 4 CLASSES
1. X-rays: the intracluster medium
2. Optical/Infrared: galaxy population
3. High-redshift clusters: evolutionary trends
4. Future surveys: detection techniques & windows
of opportunity
2

3. SUGGESTED READING
• Kravtsov & Borgani 2012
• Allen, Evrard & Mantz 2011
• Boehringer & Werner 2011
• Lutz 2014
• Peterson & Fabian 2006
• Renzini 2006
• Voit 2005
• Treu 2003
• Rosati, Borgani & Norman 2002
• Sarazin 1988
3

4. OUTLINE - LECTURE 1
• The constituents of Galaxy Clusters: Dark matter &
Baryons
• The formation of Galaxy Clusters
• Properties of the Intracluster Medium
• Cool core clusters
• Merging clusters
• X-ray scaling relations
4

5. HISTORICAL PERSPECTIVE
!
• The earliest systematic study of the properties of clusters was done by George
Abell in 1958 who compiled a complete catalog of 2712 (!) rich clusters of galaxies
by visual inspection of 104 deg2 observed by the Palomar Sky Survey
“GALAXY CLUSTERS ARETHE LARGEST,
GRAVITATIONALLY BOUND SYSTEMS INTHE
UNIVERSE”
5

6. HISTORICAL PERSPECTIVE
!
• The earliest systematic study of the properties of clusters was done by George
Abell in 1958 who compiled a complete catalog of 2712 (!) rich clusters of galaxies
by visual inspection of 104 deg2 observed by the Palomar Sky Survey
“GALAXY CLUSTERS ARETHE LARGEST,
GRAVITATIONALLY BOUND SYSTEMS INTHE
UNIVERSE”
5
• Size: radius ~ 1-2 Mpc
• Mass: 1013-1015 M☉
•Last structures to form and virialize zf ~2-3

7. HISTORICAL PERSPECTIVE
!
• The earliest systematic study of the properties of clusters was done by George
Abell in 1958 who compiled a complete catalog of 2712 (!) rich clusters of galaxies
by visual inspection of 104 deg2 observed by the Palomar Sky Survey
“GALAXY CLUSTERS ARETHE LARGEST,
GRAVITATIONALLY BOUND SYSTEMS INTHE
UNIVERSE”
5
• Size: radius ~ 1-2 Mpc
• Mass: 1013-1015 M☉
•Last structures to form and virialize zf ~2-3
APPLICATIONS IN ASTRONOMY
!
• Clusters are important Astrophysical Laboratories (e.g., galaxy formation & evolution)
• Clusters are sensitive Cosmological Probes ➔ see B. Sartoris’ and P. Rosati’s talks

8. In the current paradigm of structure formation, clusters are thought to form via a
hierarchical sequence of mergers and accretion of smaller systems driven by gravity &
dark matter that dominates the gravitational field.
During collapse the gas is heated to high temperatures (>107 K) by adiabatic compression
and shocks, then settles in hydrostatic equilibrium within cluster potential well.
CLUSTER FORMATION
credit: H. Boehringer
6
Collapse from initial density fluctuations

9. 7
Virialization timescale and virial mass
Dynamical Time Scale: the time it takes for the cluster to communicate with itself
through its own potential. The most convenient way to define the dynamical timescale
is in terms of the crossing time, the time it takes one galaxy to perform one orbit in
the cluster:
tcross = rcl / σ rcl = characteristic cluster radius, σ = velocity dispersion
Observations showed that rich clusters have a typical velocity dispersion along the line-
of-sight of σ ~ 1000 km/s and a radius of 1 Mpc.
CLUSTER FORMATION

10. 7
Virialization timescale and virial mass
Dynamical Time Scale: the time it takes for the cluster to communicate with itself
through its own potential. The most convenient way to define the dynamical timescale
is in terms of the crossing time, the time it takes one galaxy to perform one orbit in
the cluster:
tcross = rcl / σ rcl = characteristic cluster radius, σ = velocity dispersion
Local clusters (z=0, ~13.7 Gyr ) have had plenty of time to dynamically relax!
Observations showed that rich clusters have a typical velocity dispersion along the line-
of-sight of σ ~ 1000 km/s and a radius of 1 Mpc.
CLUSTER FORMATION
1 Gyr << tH

11. 7
Virialization timescale and virial mass
Dynamical Time Scale: the time it takes for the cluster to communicate with itself
through its own potential. The most convenient way to define the dynamical timescale
is in terms of the crossing time, the time it takes one galaxy to perform one orbit in
the cluster:
tcross = rcl / σ rcl = characteristic cluster radius, σ = velocity dispersion
Local clusters (z=0, ~13.7 Gyr ) have had plenty of time to dynamically relax!
Observations showed that rich clusters have a typical velocity dispersion along the line-
of-sight of σ ~ 1000 km/s and a radius of 1 Mpc.
CLUSTER FORMATION
1 Gyr << tH
Assuming virial equilibrium, 2T + U = 0,
2x ½ M v2 = G M2 / r ➔ M = 3 r σ2 / G
(for spherically symmetric systems with
gaussian velocity distribution <v2>=3σr
2)

12. 7
Virialization timescale and virial mass
Dynamical Time Scale: the time it takes for the cluster to communicate with itself
through its own potential. The most convenient way to define the dynamical timescale
is in terms of the crossing time, the time it takes one galaxy to perform one orbit in
the cluster:
tcross = rcl / σ rcl = characteristic cluster radius, σ = velocity dispersion
Local clusters (z=0, ~13.7 Gyr ) have had plenty of time to dynamically relax!
Observations showed that rich clusters have a typical velocity dispersion along the line-
of-sight of σ ~ 1000 km/s and a radius of 1 Mpc.
CLUSTER FORMATION
1 Gyr << tH
Assuming virial equilibrium, 2T + U = 0,
2x ½ M v2 = G M2 / r ➔ M = 3 r σ2 / G
the typical cluster mass is:
(for spherically symmetric systems with
gaussian velocity distribution <v2>=3σr
2)

13. 8

14. THE CONSTITUENTS OF GALAXY CLUSTERS
Dark matter halo
Accounts for 85% of cluster mass. Unknown particle most probably composed of
weakly interacting massive particles (WIMPs) that interact only through gravity
and the weak force.
Measurement of DM mass by indirect measurements, e.g, weak lensing.
Baryons
Intracluster medium: hot, optically thin gas,
85% of baryons, emits X-ray radiation.
Galaxies: tens to hundreds of galaxies, 15% of
baryons, seen in the optical. Galaxies trace the
DM distribution
stars
2%
ICM
13%
DM
85%
9

15. The overall dynamics of clusters is dominated by dark matter, which is subject only to gravity.
Considering a purely gravitational scenario and assuming that gas follows the dark matter
collapse, clusters are expected to form a regular population, hence a self-similar model emerged to
characterize clusters in a simple and convenient way:
Large systems are made of smaller identical systems Kaiser (1986)
!
In the spherical collapse approximation, a cluster has the well defined boundary corresponding to
Δ= 18π2 ∼200, where Δ is defined as the density contrast with respect to the critical density of
the Universe at the cluster redshift, ρc ≡3H2(z)/8πG.
THE SELF-SIMILAR MODEL

16. The overall dynamics of clusters is dominated by dark matter, which is subject only to gravity.
Considering a purely gravitational scenario and assuming that gas follows the dark matter
collapse, clusters are expected to form a regular population, hence a self-similar model emerged to
characterize clusters in a simple and convenient way:
Large systems are made of smaller identical systems Kaiser (1986)
!
In the spherical collapse approximation, a cluster has the well defined boundary corresponding to
Δ= 18π2 ∼200, where Δ is defined as the density contrast with respect to the critical density of
the Universe at the cluster redshift, ρc ≡3H2(z)/8πG.
THE SELF-SIMILAR MODEL
The critical density is the value
required to have a flat Universe

17. The overall dynamics of clusters is dominated by dark matter, which is subject only to gravity.
Considering a purely gravitational scenario and assuming that gas follows the dark matter
collapse, clusters are expected to form a regular population, hence a self-similar model emerged to
characterize clusters in a simple and convenient way:
Large systems are made of smaller identical systems Kaiser (1986)
!
In the spherical collapse approximation, a cluster has the well defined boundary corresponding to
Δ= 18π2 ∼200, where Δ is defined as the density contrast with respect to the critical density of
the Universe at the cluster redshift, ρc ≡3H2(z)/8πG.
THE SELF-SIMILAR MODEL
In reality, the cluster mass is not a well-defined quantity: clusters are not closed spheres, however,
it is convenient to define a cluster as the mass enclosed in a radius corresponding to a fixed Δ,
with respect to ρc:
The critical density is the value
required to have a flat Universe

18. The overall dynamics of clusters is dominated by dark matter, which is subject only to gravity.
Considering a purely gravitational scenario and assuming that gas follows the dark matter
collapse, clusters are expected to form a regular population, hence a self-similar model emerged to
characterize clusters in a simple and convenient way:
Large systems are made of smaller identical systems Kaiser (1986)
!
In the spherical collapse approximation, a cluster has the well defined boundary corresponding to
Δ= 18π2 ∼200, where Δ is defined as the density contrast with respect to the critical density of
the Universe at the cluster redshift, ρc ≡3H2(z)/8πG.
THE SELF-SIMILAR MODEL
Self-similarity in the cluster properties allows us to deduce all other cluster properties from the
observation of a single global cluster parameter (e.g. X-ray luminosity).
In reality, the cluster mass is not a well-defined quantity: clusters are not closed spheres, however,
it is convenient to define a cluster as the mass enclosed in a radius corresponding to a fixed Δ,
with respect to ρc:
The critical density is the value
required to have a flat Universe

19. The overall dynamics of clusters is dominated by dark matter, which is subject only to gravity.
Considering a purely gravitational scenario and assuming that gas follows the dark matter
collapse, clusters are expected to form a regular population, hence a self-similar model emerged to
characterize clusters in a simple and convenient way:
Large systems are made of smaller identical systems Kaiser (1986)
!
In the spherical collapse approximation, a cluster has the well defined boundary corresponding to
Δ= 18π2 ∼200, where Δ is defined as the density contrast with respect to the critical density of
the Universe at the cluster redshift, ρc ≡3H2(z)/8πG.
THE SELF-SIMILAR MODEL
“Disclaimer”:
non-linear processes of collapse + dissipative physics of baryons cause deviations from self-similarity
Self-similarity in the cluster properties allows us to deduce all other cluster properties from the
observation of a single global cluster parameter (e.g. X-ray luminosity).
In reality, the cluster mass is not a well-defined quantity: clusters are not closed spheres, however,
it is convenient to define a cluster as the mass enclosed in a radius corresponding to a fixed Δ,
with respect to ρc:
The critical density is the value
required to have a flat Universe

20. DARK MATTER & BARYONS
comparison between DM simulation and X-ray gas simulation
11

21. 12

22. THE INTRACLUSTER MEDIUM:
!
X-RAY OBSERVATIONS
XMM-NewtonChandra
13

23. THE ICM
In their formation process, galaxy clusters undergo adiabatic compression & shocks
providing the primordial heat to the intracluster medium, a hot gas confined by the
cluster’s gravitational potential well.
!
Clusters are permeated by this low-density plasma, which strongly emits X-ray radiation:
Boehringer & Werner 2013
• free-free: thermal bremsstrahlung
• free-bound: recombination
• bound-bound: deexcitation radiation
continuum
➔ line emission

24. THE ICM
In their formation process, galaxy clusters undergo adiabatic compression & shocks
providing the primordial heat to the intracluster medium, a hot gas confined by the
cluster’s gravitational potential well.
!
Clusters are permeated by this low-density plasma, which strongly emits X-ray radiation:
Boehringer & Werner 2013
• free-free: thermal bremsstrahlung
• free-bound: recombination
• bound-bound: deexcitation radiation
continuum
➔ line emission
Main emission processes: thermal Bremsstrahlung radiation and metal emission lines,
proportional to the square of the gas density:

25. THE ICM
In their formation process, galaxy clusters undergo adiabatic compression & shocks
providing the primordial heat to the intracluster medium, a hot gas confined by the
cluster’s gravitational potential well.
!
Clusters are permeated by this low-density plasma, which strongly emits X-ray radiation:
Boehringer & Werner 2013
• free-free: thermal bremsstrahlung
• free-bound: recombination
• bound-bound: deexcitation radiation
continuum
➔ line emission
Main emission processes: thermal Bremsstrahlung radiation and metal emission lines,
proportional to the square of the gas density:

26. THE ICM
In their formation process, galaxy clusters undergo adiabatic compression & shocks
providing the primordial heat to the intracluster medium, a hot gas confined by the
cluster’s gravitational potential well.
!
Clusters are permeated by this low-density plasma, which strongly emits X-ray radiation:
Boehringer & Werner 2013
• free-free: thermal bremsstrahlung
• free-bound: recombination
• bound-bound: deexcitation radiation
continuum
➔ line emission
Integrating εν over the X-ray emission energy range &
gas distribution, we obtain LX ~ 1043-1045 erg s-1.
Main emission processes: thermal Bremsstrahlung radiation and metal emission lines,
proportional to the square of the gas density:

27. THE ICM
In their formation process, galaxy clusters undergo adiabatic compression & shocks
providing the primordial heat to the intracluster medium, a hot gas confined by the
cluster’s gravitational potential well.
!
Clusters are permeated by this low-density plasma, which strongly emits X-ray radiation:
Boehringer & Werner 2013
• free-free: thermal bremsstrahlung
• free-bound: recombination
• bound-bound: deexcitation radiation
Optically thin plasma (no radiative transfer)
T ~ 2-10 keV
ρ
The gas is chemically enriched by, mostly, SN Ia
continuum
➔ line emission
Integrating εν over the X-ray emission energy range &
gas distribution, we obtain LX ~ 1043-1045 erg s-1.
Main emission processes: thermal Bremsstrahlung radiation and metal emission lines,
proportional to the square of the gas density:

28. THE ICM
In their formation process, galaxy clusters undergo adiabatic compression & shocks
providing the primordial heat to the intracluster medium, a hot gas confined by the
cluster’s gravitational potential well.
!
Clusters are permeated by this low-density plasma, which strongly emits X-ray radiation:
Boehringer & Werner 2013
• free-free: thermal bremsstrahlung
• free-bound: recombination
• bound-bound: deexcitation radiation
Optically thin plasma (no radiative transfer)
T ~ 2-10 keV
ρ
The gas is chemically enriched by, mostly, SN Ia
continuum
➔ line emission
mean cosmic ρ
baryons ~10-8 cm-3 !
Integrating εν over the X-ray emission energy range &
gas distribution, we obtain LX ~ 1043-1045 erg s-1.
Main emission processes: thermal Bremsstrahlung radiation and metal emission lines,
proportional to the square of the gas density:

29. THE ICM
Plasma radiation codes:
!
• MEKAL (Mewe et al. 1995)
• APEC (Smith et al. 2001)
implemented in XSPEC, an X-Ray Spectral Fitting Package, http://heasarc.nasa.gov/xanadu/xspec/
15
Boehringer & Werner 2013
bremsstrahlung
2ph transition
recombination
T increases
!
Bremsstrahlung dominates shape of continuum spectrum

30. THE ICM X-RAY SPECTRUM
•The shape of the spectrum is a function of the temperature & chemical
composition and its normalization is proportional to the plasma density
the element abundances are derived from the intensity of the spectral lines
temperature is derived from the continuum (Bremsstrahlung)
•Observed radiation is the result of an integral of radiative emission along the line of
sight -> need to deproject the spectrum to obtain deprojected temperature, gas
density and metalicity profiles (e.g. projct, XSPEC):
requires very good photon statistics + angular resolution
better than radial binning used
assume 3D spherical symmetry
fit spectra extracted from a series of concentric annuli simultaneously
to account for projection effect

31. THE ICM X-RAY SPECTRUM
•The shape of the spectrum is a function of the temperature & chemical
composition and its normalization is proportional to the plasma density
the element abundances are derived from the intensity of the spectral lines
temperature is derived from the continuum (Bremsstrahlung)
•Observed radiation is the result of an integral of radiative emission along the line of
sight -> need to deproject the spectrum to obtain deprojected temperature, gas
density and metalicity profiles (e.g. projct, XSPEC):
requires very good photon statistics + angular resolution
better than radial binning used
assume 3D spherical symmetry
fit spectra extracted from a series of concentric annuli simultaneously
to account for projection effect
often we have to rely on projected temperature profiles
and in the worst case we can only measure a single T

32. CHEMICAL ENRICHMENT OFTHE ICM
!
•The ICM of local clusters has a typical average metallicity of 0.3 Z⦿
•The deep gravitational potential wells of clusters lock metals produced by member
galaxies: the ICM is a fossil record of the chemical enrichment of the Universe
17

33. CHEMICAL ENRICHMENT OFTHE ICM
!
•The ICM of local clusters has a typical average metallicity of 0.3 Z⦿
•The deep gravitational potential wells of clusters lock metals produced by member
galaxies: the ICM is a fossil record of the chemical enrichment of the Universe
17
!
• Fe- group elements from SN Ia
• Most prominent signature of the metal
enrichment is the Fe K-line complex at 6.7 keV
(the only accessible line at high-z)
• α - elements (O, Ne, Mg) originate from core
collapse supernova (SN II)
2A 0335+096
Werner et al. 2006

34. CHEMICAL ENRICHMENT OFTHE ICM
!
•The ICM of local clusters has a typical average metallicity of 0.3 Z⦿
•The deep gravitational potential wells of clusters lock metals produced by member
galaxies: the ICM is a fossil record of the chemical enrichment of the Universe
17
!
• Fe- group elements from SN Ia
• Most prominent signature of the metal
enrichment is the Fe K-line complex at 6.7 keV
(the only accessible line at high-z)
• α - elements (O, Ne, Mg) originate from core
collapse supernova (SN II)
2A 0335+096
Werner et al. 2006
!
• Main agents of metal ejection:
• star formation in the brightest cluster
galaxy (BCG) ➔ Fe peak De Grandi et al 2004
!
• primordial enrichment of the ISM before cluster virialization

35. PROPERTIES OFTHE ICM
Density contrast
To determine global cluster parameters, we need a fiducial radius.
The characteristic or fiducial / virial radius RV of a cluster, defined from the
theory of structure collapse in an expanding Universe is the radius at which the
mean density of the cluster is, Δ = 200 x ρcrit.
ρc = 3 H2 / 8π G
18

36. PROPERTIES OFTHE ICM
Density contrast
To determine global cluster parameters, we need a fiducial radius.
The characteristic or fiducial / virial radius RV of a cluster, defined from the
theory of structure collapse in an expanding Universe is the radius at which the
mean density of the cluster is, Δ = 200 x ρcrit.
ρc = 3 H2 / 8π G
Rvir = R200 ~ 1 Mpc
R500
R2500 (core)
18

37. PROPERTIES OFTHE ICM
Surface brightness Zhang et al 2006
Sx is a projected quantity.
Invoking spherical symmetry
we can deproject Sx to obtain
a measure of the ICM density.
19

38. PROPERTIES OFTHE ICM
Surface brightness Zhang et al 2006
Sx is a projected quantity.
Invoking spherical symmetry
we can deproject Sx to obtain
a measure of the ICM density.
19
Beta model approximation:
!
S0 = the central surface brightness, rc =
the core radius, C = constant background
Cavaliere & Fusco Femiano 1976

39. PROPERTIES OFTHE ICM
Temperature profiles
Pratt et al 2007
20

40. PROPERTIES OFTHE ICM
Cooling time
gas enthalpy / energy lost per volume
Sanderson et al 2006
tcool≣(dlnTgas/dt)-1
Λ(T) = cooling function
ng = gas number density
ne = electron number density
T = temperature
21

41. PROPERTIES OFTHE ICM
Entropy
Cavagnolo et al 2009
Entropy originates mostly from the
formation shock heating of the ICM.
!
22
K ≣ kB T ne
-⅔

42. PROPERTIES OFTHE ICM
Entropy
Cavagnolo et al 2009
Entropy originates mostly from the
formation shock heating of the ICM.
!
22
K ≣ kB T ne
-⅔
shock heating

43. PROPERTIES OFTHE ICM
Entropy
Cavagnolo et al 2009
Entropy originates mostly from the
formation shock heating of the ICM.
!
22
K ≣ kB T ne
-⅔
“Preheating”: entropy excess of IGM
before the formation of the cluster
caused by early energy injection by
star burst episodes, required to
explain observations
ΔK ~ 100 keV cm2 entropy floor
preheating shock heating

44. COOL CORE CLUSTERS
23

45. BEFORE ADVENT OF XMM-NEWTON
If gas cools radiatively in an undisturbed
manner then we have the standard
isobaric cooling-flow model, produced by
summing collisionally-ionized X-ray spectra
!
Model prediction: lots of emission line
radiation, in particular, Fe XVII which is
emitted below 1 keV.
!
Peterson & Fabian 2006
Cooling flows
24

46. BEFORE ADVENT OF XMM-NEWTON
If gas cools radiatively in an undisturbed
manner then we have the standard
isobaric cooling-flow model, produced by
summing collisionally-ionized X-ray spectra
!
Model prediction: lots of emission line
radiation, in particular, Fe XVII which is
emitted below 1 keV.
!
Peterson & Fabian 2006
Cooling flows
24
problem: no cooling flows!

47. CC nCC
SIGNATURES OF COOL CORE CLUSTERS
25
Central surface brightness peak

48. 26
Sanderson et al 2006
Central temperature drop:
Tcore ~ ⅓ - ½ Tbulk
!
SIGNATURES OF COOL CORE CLUSTERS

49. Cavagnolo et al. 2009
Cool core - - - -
Non cool core - . - .
27
Cool cores have lower central entropy
Central entropy threshold:
K0 < 30 keV cm2
!
SIGNATURES OF COOL CORE CLUSTERS

50. De Grandi & Molendi 2004
● Cool Core
◦ non-Cool core
28
Central Iron abundance:
ZFe up to solar value &
beyond
<ZFe> ~ 0.3 Z☉
SIGNATURES OF COOL CORE CLUSTERS

51. !
Cool cores have lower central cooling time
Central cooling time << tHubble
SIGNATURES OF COOL CORE CLUSTERS

52. AGN Feedback
The ICM cools down radiatively towards the center, unless a feedback mechanism
prevents it! e.g. Fabian 2012
• Heating counteracts cooling -> AGN energy injection
• Enough energy released from AGN jets to stop star formation, but:
• how is heat gently distributed?
• are these periodic episodes?
• Feedback mechanisms between ICM and BCG
• Why do we have non-cool cores? AGN heating
overshoot? Major mergers?
COOL CORE CLUSTERS
30
Local universe (z~0) is dominated by CC: 50-70%, tcool e.g. Hudson+2010

53. FEEDBACK IN ACTION: JETS & BUBBLES
!
Deep ~500 ks Chandra X-ray image
(blue) andVLA 330 MHz radio image
(red) superposed with the HST image
of the galaxy cluster MS0735+7421.
The giant X-ray cavities, filled with
radio emission, are surrounded by a
cocoon shock.The box is ~ 800 x 800
kpc.
31
Gitti et al. 2012

54. Fabian et al. 2011
FEEDBACK IN ACTION: JETS & BUBBLES
Perseus cluster
32
!
~1 Msec Chandra X-ray image
rising bubbles
of relativistic
plasma from
the radio jets

55. 33
Perseus cluster - NGC 1275 Hα filaments - star formation
FEEDBACK IN ACTION: JETS & BUBBLES

56. MERGING CLUSTERS
34

57. Non cool cores make up ~50% of local clusters. Most show a disturbed ICM
morphology indicative of mergers.
!
Cluster mergers are the most energetic events in the Universe after the Big Bang.
Subclusters collide at velocities of ~2000 km/s, releasing gravitational binding energy of
>1064 ergs. Shocks heat & compress ICM.
35
2002 book edited by Feretti, Gioia, Giovannini
MERGING CLUSTERS

58. Non cool cores make up ~50% of local clusters. Most show a disturbed ICM
morphology indicative of mergers.
!
Cluster mergers are the most energetic events in the Universe after the Big Bang.
Subclusters collide at velocities of ~2000 km/s, releasing gravitational binding energy of
>1064 ergs. Shocks heat & compress ICM.
35
2002 book edited by Feretti, Gioia, Giovannini
MERGING CLUSTERS
!
• Observational evidence that mergers disrupt (partially) cool cores:
presence of substructures, high cooling rates, high entropy
• Simulations indicate that the preferred channels to disrupt a cool core is through ICM heating
caused by merger shocks and ram pressure of the merging sub cluster

59. Non cool cores make up ~50% of local clusters. Most show a disturbed ICM
morphology indicative of mergers.
!
Cluster mergers are the most energetic events in the Universe after the Big Bang.
Subclusters collide at velocities of ~2000 km/s, releasing gravitational binding energy of
>1064 ergs. Shocks heat & compress ICM.
35
2002 book edited by Feretti, Gioia, Giovannini
MERGING CLUSTERS
!
• Observational evidence that mergers disrupt (partially) cool cores:
presence of substructures, high cooling rates, high entropy
• Simulations indicate that the preferred channels to disrupt a cool core is through ICM heating
caused by merger shocks and ram pressure of the merging sub cluster
!
• Thermal effects of mergers:
substructure / cold fronts /merger shocks
Cold fronts: sharp surface brightness discontinuities in merging
clusters. Unlike merger shocks there is no pressure jump and
the gas temperature in cold fronts is cold.
Cold + dense gas ➔ low entropy
!
hot diffuse gas
Cold front
!
!
!
cool, dense gas

60. !
Thermodynamic maps for
the ICM of the Bullet
Sx T
P K
Cold front
Merger

61. !
Thermodynamic maps for
the ICM of the Bullet
Sx T
P K
Velocity shock across the jump, measured from the temperatures on either side of the of the shock:
Δvs=v1- v2 = [ (kT1/μmp) (C -1) (T2/T1 - 1/C) ] (Markevitch 1999)
C= shock compression
Cold front
Merger

62. MERGING CLUSTERS
37
!
• Soft X-ray emission (“soft excess”): Inverse Compton scattering of CMB photons by
low E relativistic e-
!
• Hard X-ray tails (>20 kev) short lived, Inverse Compton scattering of CMB photons by
high E relativistic e-
!
• High energy cosmic rays
!
Problem: how do you measure the cluster mass ? Hydrostatic equilibrium is not verified
➔ Weak lensing (P. Rosati talk)
Non thermal effects of mergers:
!
• Large scale diffuse radio sources not connected with individual
galaxies produced by high E relativistic e-
• radio halo if located in the cluster center
• radio relic if located in the outskirts
Radio relic in Abell 3667
Röttgering et al.1997

63. SCALING RELATIONS
Compilation of scaling relations
by Giodini et al 2013
Correlating ICM observables &
mass via power laws
!
Key ingredient in the use of
clusters as cosmological probes
!
Clusters as a self similar family
!
38

64. SCALING RELATIONS
Compilation of scaling relations
by Giodini et al 2013
Correlating ICM observables &
mass via power laws
!
Key ingredient in the use of
clusters as cosmological probes
!
Clusters as a self similar family
!
38
!
Understand origin of scatter:
Need to excise cores to measure
Lx andT (non grav processes)

65. GALAXIES IN CLUSTERS:
!
OPTICAL AND INFRARED
OBSERVATIONS
39

66. OUTLINE - LECTURE 2
• Properties of galaxies in clusters
• morphology
• color magnitude relation
• SED fitting: galaxy ages, SFHs, attenuation,…
• star formation
• Environmental processes in clusters
• The Brightest Cluster Galaxy
40

67. MORPHOLOGY
Hubble tuning fork diagram
41

68. MORPHOLOGY
Hubble tuning fork diagram
41
Ell + S0 are typically the most
relevant for cluster studies

69. EARLYVS. LATETYPE GALAXIES
Early-types
bulge dominated, typically ellipticals and S0s
massive (up to few 1012 M☉)
redder colors
passive: star formation quenched (“dead”)
spectral features: D4000 break, Mg absorption lines
!
Late-types
disky
bluer colors
spectral features: emission lines, e.g., Hα
on-going star forming
42

70. MORPHOLOGY
Model approach: structural parameters
The Sersic model
!
!
for n=4, DeVaucouleurs model
!
Caveat: degeneracy between n and re
Ellipticals have high index n (>2)
Disky galaxies have low index n (<2) and require an additional model
component (exponential disk) for proper description
available software that performs galaxy model fitting (𝜒2):
GALFIT, GIM2D, BUDDA, …
Σ: surface brightness at radius r
n indicates the concentration of the profile
re encloses half of the galaxy light
43

71. MORPHOLOGY
Morphology-density relation
Dressler 1980
the fraction of galaxies of different
morphological types in a region depends
on the overall density of the environment.
E
S0
Sp
44
outskirts core
Local galaxy density: distance to the nth nearest neighbor, e.g. Σ

72. MORPHOLOGY
Morphology-density relation
Dressler 1980
the fraction of galaxies of different
morphological types in a region depends
on the overall density of the environment.
E
S0
Sp
44
outskirts core
Local galaxy density: distance to the nth nearest neighbor, e.g. Σ
The fraction of spiral galaxies falls for
increasing local density, compensated by
a rise in the fraction of elliptical + S0s.
The cores of clusters are dominated by
EarlyType Galaxies.

73. ENVIRONMENT
projected cluster centric distance Treu et al. 2003
Physical processes affecting galaxy morphological transformation &
evolution
•Galaxy interactions with the cluster potential well. Tidal compression of galactic gas
by interaction with the cluster potential can increase the star formation rate; Tidal stripping of the
outer galactic regions (e.g. the DM halos) by the cluster potential. Time scales 108 - 109 yrs
• Galaxy-Galaxy interactions:
- Mergers (low speed interactions
between galaxies of similar mass)
- Harassment (high speed interactions
between galaxies)
45
• Galaxy interactions with the ICM:
- starvation: decrease of star formation, few Gyrs
- ram-pressure stripping: removal of galactic gas by
pressure exerted by the intracluster medium
(short time scales ~107-8yrs)

74. ENVIRONMENT
46
MUSE/VLT reveals the motions of the material.
The outskirts of ESO 137-001 are already
completely devoid of gas (Fumagalli +2014)
NASA/ESA Hubble + Chandra (blue)
Ram pressure stripping in the spiral galaxy ESO 137-001 in Abell 3627

75. Bower et al. 1999
PROPERTIES OF GALAXIES IN CLUSTERS
The COLOR-MAGNITUDE RELATION, CMR
Galaxy clusters are characterized by an old population of passively evolving galaxies, forming a
distinct and tight sequence of galaxies in the color-magnitude relation, the red-sequence (Baum
(1959),Visvanathan & Sandage (1977).
47

76. Bower et al. 1999
PROPERTIES OF GALAXIES IN CLUSTERS
The COLOR-MAGNITUDE RELATION, CMR
Galaxy clusters are characterized by an old population of passively evolving galaxies, forming a
distinct and tight sequence of galaxies in the color-magnitude relation, the red-sequence (Baum
(1959),Visvanathan & Sandage (1977).
In addition to the RS, a distinct
population of blue late-type
galaxies is also present in the
CMR of galaxy clusters, evidencing
a color bimodality strongly
dependent on the stellar content
of galaxies Strateva et al. (2001).
47

77. Bower et al. 1999
PROPERTIES OF GALAXIES IN CLUSTERS
The COLOR-MAGNITUDE RELATION, CMR
Galaxy clusters are characterized by an old population of passively evolving galaxies, forming a
distinct and tight sequence of galaxies in the color-magnitude relation, the red-sequence (Baum
(1959),Visvanathan & Sandage (1977).
In addition to the RS, a distinct
population of blue late-type
galaxies is also present in the
CMR of galaxy clusters, evidencing
a color bimodality strongly
dependent on the stellar content
of galaxies Strateva et al. (2001).
47
CMR parameters:
zero point (age of cluster)
scatter of RS (galaxy age
variations)
slope (related w/ metal content)

78. PROPERTIES OF GALAXIES IN CLUSTERS
The COLOR-MAGNITUDE RELATION, CMR
!
• Red-sequence as a “cheap” photometric redshift: only 2 bands
!
• Choose efficient combination of filters to obtain a color that is sensitive to the cluster redshift
!
48
Redshift evolution of several colors (efficiency)

79. PROPERTIES OF GALAXIES IN CLUSTERS
The COLOR-MAGNITUDE RELATION, CMR
!
• Red-sequence as a “cheap” photometric redshift: only 2 bands
!
• Choose efficient combination of filters to obtain a color that is sensitive to the cluster redshift
!
48
Redshift evolution of several colors (efficiency)
!
!
Technical aspects of measuring gal. colors:
• match pixel scales of images,
• correct the blurring PSF of different filters
(degrade images to the worst PSF)
(e.g. IRAF package)
!
• Perform source detection and photometry
(e.g. SExtractor program)
!
• Colors are measured in small apertures, just
beyond the PSF: avoid color gradients

80. SYNTHETIC STELLAR populations
Technique to study the stellar content in galaxies, to constrain
• stellar masses
• ages
• star formation histories
• Models based on stellar evolution theory assume a Simple Stellar Population (SSP)
where a single burst of star formation took place, with equal metallicity.
!
• More realistically, the star formation history of galaxies (SFH) is likely due to a series of
instantaneous bursts, therefore their stellar population is better described with
composite SSPs (diff. ages).
!
• Choose the initial mass function (IMF), describing the relative frequency with which
stars of various masses are formed (e.g. Salpeter 1955, Chabrier 2003).
49
Many popular libraries: Bruzual & Charlot (2003), Maraston (2005), …
PROPERTIES OF GALAXIES IN CLUSTERS

81. SYNTHETIC STELLAR POPULATIONS:
STAR FORMATION HISTORIES
The SFHs of local galaxies:
Field galaxies 1 - 2 Gyr younger than
their counterparts in clusters
cluster
field
Thomas et al. 200550

82. SYNTHETIC STELLAR POPULATIONS:
STAR FORMATION HISTORIES
The SFHs of local galaxies:
Field galaxies 1 - 2 Gyr younger than
their counterparts in clusters
SFHs are mass dependent: the more
massive elliptical galaxies have SFHs
peaking at higher redshifts (z≥3 in
clusters) than less massive systems.
➔ Conflict w/ expectations based on
the hierarchical growth of DM haloes.
!
Solution: allow a late mass assembly via
dry mergers, where small gas-free
galaxies merge to form larger galaxies
➔ stars in massive galaxies are old, even
if they formed recently.
cluster
field
Thomas et al. 200550

83. STAR FORMATION
e.g. review by Calzetti 2012, Kennicutt & Evans 2012
51
Star formation indicators:
1. Ultraviolet flux: high mass stars dominate
2. Optical emission lines:
Hα λ6563
OII λ3727
!
!
The youngest stellar populations emit the bulk of their energy in the UV (rest-frame)

84. STAR FORMATION
e.g. review by Calzetti 2012, Kennicutt & Evans 2012
51
Star formation indicators:
1. Ultraviolet flux: high mass stars dominate
2. Optical emission lines:
Hα λ6563
OII λ3727
!
!
sensitive to dust need independent
assessment of dust, SED fitting or Balmer
decrement: Hα/Hβ
The youngest stellar populations emit the bulk of their energy in the UV (rest-frame)

85. STAR FORMATION
e.g. review by Calzetti 2012, Kennicutt & Evans 2012
51
Star formation indicators:
1. Ultraviolet flux: high mass stars dominate
2. Optical emission lines:
Hα λ6563
OII λ3727
!
!
sensitive to dust need independent
assessment of dust, SED fitting or Balmer
decrement: Hα/Hβ
contamination by AGN
The youngest stellar populations emit the bulk of their energy in the UV (rest-frame)

86. STAR FORMATION
e.g. review by Calzetti 2012, Kennicutt & Evans 2012
51
Star formation indicators:
1. Ultraviolet flux: high mass stars dominate
2. Optical emission lines:
Hα λ6563
OII λ3727
!
!
sensitive to dust need independent
assessment of dust, SED fitting or Balmer
decrement: Hα/Hβ
contamination by AGN
The youngest stellar populations emit the bulk of their energy in the UV (rest-frame)
Most of the star formation at z~1 is enshrouded in dust
3. Far infrared emission: dust absorbs UV very efficiently and reradiates in FIR
dust as a calorimeter that re-emits the total radiation from young stars

87. STAR FORMATION
52
Calibrations: empirical/model-based relations used to convert L to SFRs
the conversion from luminosity to SFR assumes:
• the SFR has been roughly constant over the timescale probed by the specific emission used
• the stellar IMF is known and fully sampled (hi-lo mass) assumption: IMF is constant & universal
• Kroupa 2001 χ(M) = dN/dM = A M-1.3 0.1 < M/M⦿ < 0.5
= 0.5 A M-1.3 0.5 < M/M⦿ < 100
• Chabrier 2003 log-normal dist. χ(M) = A e-(log m - log mc)2/2σ2 M/M⦿ < 1
= B M-1.3 M/M⦿ > 1
• Salpeter 1955 χ(M) = A M-2.35 0.1 < M/M⦿ < 100

88. STAR FORMATION
52
Calibrations: empirical/model-based relations used to convert L to SFRs
the conversion from luminosity to SFR assumes:
• the SFR has been roughly constant over the timescale probed by the specific emission used
• the stellar IMF is known and fully sampled (hi-lo mass) assumption: IMF is constant & universal
• Kroupa 2001 χ(M) = dN/dM = A M-1.3 0.1 < M/M⦿ < 0.5
= 0.5 A M-1.3 0.5 < M/M⦿ < 100
• Chabrier 2003 log-normal dist. χ(M) = A e-(log m - log mc)2/2σ2 M/M⦿ < 1
= B M-1.3 M/M⦿ > 1
• Salpeter 1955 χ(M) = A M-2.35 0.1 < M/M⦿ < 100 most widely used

89. STAR FORMATION
52
Calibrations: empirical/model-based relations used to convert L to SFRs
the conversion from luminosity to SFR assumes:
• the SFR has been roughly constant over the timescale probed by the specific emission used
• the stellar IMF is known and fully sampled (hi-lo mass) assumption: IMF is constant & universal
• Kroupa 2001 χ(M) = dN/dM = A M-1.3 0.1 < M/M⦿ < 0.5
= 0.5 A M-1.3 0.5 < M/M⦿ < 100
• Chabrier 2003 log-normal dist. χ(M) = A e-(log m - log mc)2/2σ2 M/M⦿ < 1
= B M-1.3 M/M⦿ > 1
• Salpeter 1955 χ(M) = A M-2.35 0.1 < M/M⦿ < 100
calibrations based on evolutionary
synthesis models, in which the SEDs are
derived for synthetic stellar populations
with a prescribed age mix, chemical
composition, and IMF
SFR = log Lx - log Cx [M⦿/yr]
Most recent set of calibrations
Kennicutt & Evans 2012
most widely used

90. Far-infrared emission
Herschel Space Observatory
(Pilbratt et al 2010)
!
PACS 70-100-160 μm
SPIRE 250-350-500 μm
SED of typical SF galaxy
STAR FORMATION: FAR INFRARED
53

91. Far-infrared emission
Herschel Space Observatory
(Pilbratt et al 2010)
!
PACS 70-100-160 μm
SPIRE 250-350-500 μm
SED of typical SF galaxy
STAR FORMATION: FAR INFRARED
53
!
Limitations
• angular resolution: 6” (70um) - 35” (500um) contamination
• for SPIRE: confusion limited ➔ limited sensitivity: only ULIRGs
are detected …
Galaxies are unresolved point sources in Herschel maps

92. 100um 160um
E.G. HERSCHEL DATASET OF A CLUSTER
!
250um 350um 500um

93. 55
• Source detection in PACS maps ➔ list of priors to SPIRE
!
• Aperture photometry (Sextractor) / PSF fitting (Sussextractor)
!
• Herschel fluxes ➔ total infrared luminosity, LIR: FIR SED fitting
• SED fitting code (e.g. LePhare, Hyperz, Magphys)
• FIR SED templates, e.g. Chary & Elbaz 2001
• LIR ➔ SFR via Kennicutt 1998 law
!
!
• Match FIR detections with ancillary data
55
E.G. HERSCHEL DATA ANALYSIS BASIC
RECIPE
SFRIR (M⨀/yr) = 4.5 x 10-44 LIR (erg/s)

94. 56
• Empirical relation between stellar mass and SFR (e.g. Daddi et al 2007, Elbaz et al. 2011)
!
!
• Present at out to z~3 (at least), only zero point changes
• The amount of gas in galaxies (fuel) is what determines the path of a galaxy in
the MS plane
56
THE MAIN-SEQUENCE OF SF
2 modes of star formation are widely recognized:
!
• the gradual formation of stars in gaseous disks
➔ main sequence galaxies
!
• the high-intensity epochs of star formation known
as starbursts, expected to result from major
galaxy mergers and the sudden coalescence of
dense gas.
Rodighiero et al 2011
specific SFR = SFR/M*
SFR ∝ M*α

95. BRIGHTEST CLUSTER GALAXY, BCG
57
The central regions of massive galaxy clusters typically host a very bright and massive (1012M*)
galaxy, the brightest cluster galaxy (BCG), typically an early-type galaxy (elliptical, S0).
Formation of BCGs: simulations perspective (De Lucia & Blaizot 2007)
Local BCGs develop through the accretion of a small # of objects with M>1010 M⊙, very low gas
fractions and SFRs (dry mergers).
!
The bulk of the stars in BCGs forms early (z∼3-5),
though the final BCGs assemble from small progenitors
rather late, by z ∼ 0.5.

96. BRIGHTEST CLUSTER GALAXY, BCG
!
!
• The properties of BCGs are governed by their large
stellar content and ubiquitous location at the bottom
of the potential well of their host cluster:
!
BCGs are coincident with the peaks of X-ray emission,
are connected with the presence of a cool core and
contribute to most of the Fe content in the ICM.
57
The central regions of massive galaxy clusters typically host a very bright and massive (1012M*)
galaxy, the brightest cluster galaxy (BCG), typically an early-type galaxy (elliptical, S0).
Formation of BCGs: simulations perspective (De Lucia & Blaizot 2007)
Local BCGs develop through the accretion of a small # of objects with M>1010 M⊙, very low gas
fractions and SFRs (dry mergers).
!
The bulk of the stars in BCGs forms early (z∼3-5),
though the final BCGs assemble from small progenitors
rather late, by z ∼ 0.5.

97. HIGH REDSHIFT GALAXY
CLUSTERS:
!
OBSERVATIONS & EVOLUTION
58

98. OUTLINE - LECTURE III
• Evolutionary trends in the ICM
• Evolutionary trends in the galaxy populations
• Brightest central galaxy
• CMR
• Morphology
• SFR - reversal of the SF-density relation
• Distant cluster gallery & properties
59

99. HIGH-REDSHIFT CLUSTERS
While the local (z~0) population of clusters is fairly well studied, the distant
cluster population (z>1) remains poorly understood
!
Observational challenge: distant clusters are small (angular size, DA=(1+z)/DL)
and faint (surface brightness dimming (1+z)4): requires telescopes with large
apertures and photon collecting power.
!
Crucial to understand the formation of galaxy clusters and their
connection to proto-clusters (unvirialized galaxy systems that will collapse into a
cluster)
!
Evolutionary effects: at higher redshift we shouldn’t expect clusters to follow the
same scaling relations and have the same properties of their local counterparts
because they are much younger
!
∝
60

100. HIGH-REDSHIFT CLUSTERS
CURRENT STATUS & CHALLENGES
Cluster z ref
1 SpARCS J003550-431224 1.34 Wilson et al. 2008
2 XDCP J1532.2-0837 1.36 Suhada et al. 2011
3 ISCS J1434.7+3519 1.37 Brodwin et al. in prep
4 ISCS J1433.8+3325 1.37 Eisenhardt et al. 2008
5 XMMU J2235.3-2557 1.39 Mullis et al. 2005
6 ISCSJ143809+341419 1.41 Stanford et al. 2005
7 XMMXCS J2215.9-1738 1.46 Stanford et al. 2006
8 SPT-CL J2040-4451 1.48 Bayliss et al. 2013
9 ISCS J1432.4+3250 1.49 Brodwin et al. 2011
10 XMMU J0338.8+0021 1.49 Nastasi et al. 2011
11 XDCP J1007.3+1237 1.56 Fassbender et al. 2011
12 XDCP J0044.0-2033 1.58 Santos et al. 2011
13 ClG J0218.3-0510 1.62 Papovich et al. 2010
14 SpARCS J033056-284300 1.63 Wilson et al. in prep
15 SpARCS J022427-032354 1.63 Muzzin et al. in prep
16 IDCS J1426.5+3508 1.75 Stanford et al. 2012
17 JKCS 041 1.80 Newman et al. 2014
18 IDCS J1433.2+3306 1.89 Zeimann et al. 2012
19 Cl J1449+0856 2.0 Gobat et al. 2011
Tozzi et al. 2014

101. HIGH-REDSHIFT CLUSTERS
CURRENT STATUS & CHALLENGES
!
Major challenges:
• go beyond twentish well studied systems
originating from different surveys, to a
statistical sample.
• Measure robust cluster masses
• Census of star formation
Cluster z ref
1 SpARCS J003550-431224 1.34 Wilson et al. 2008
2 XDCP J1532.2-0837 1.36 Suhada et al. 2011
3 ISCS J1434.7+3519 1.37 Brodwin et al. in prep
4 ISCS J1433.8+3325 1.37 Eisenhardt et al. 2008
5 XMMU J2235.3-2557 1.39 Mullis et al. 2005
6 ISCSJ143809+341419 1.41 Stanford et al. 2005
7 XMMXCS J2215.9-1738 1.46 Stanford et al. 2006
8 SPT-CL J2040-4451 1.48 Bayliss et al. 2013
9 ISCS J1432.4+3250 1.49 Brodwin et al. 2011
10 XMMU J0338.8+0021 1.49 Nastasi et al. 2011
11 XDCP J1007.3+1237 1.56 Fassbender et al. 2011
12 XDCP J0044.0-2033 1.58 Santos et al. 2011
13 ClG J0218.3-0510 1.62 Papovich et al. 2010
14 SpARCS J033056-284300 1.63 Wilson et al. in prep
15 SpARCS J022427-032354 1.63 Muzzin et al. in prep
16 IDCS J1426.5+3508 1.75 Stanford et al. 2012
17 JKCS 041 1.80 Newman et al. 2014
18 IDCS J1433.2+3306 1.89 Zeimann et al. 2012
19 Cl J1449+0856 2.0 Gobat et al. 2011
Tozzi et al. 2014
• no z > 1.5 cluster from SZE
• IR surveys likely to be most successful

102. EVOLUTIONARYTRENDS
INTHE ICM

103. Evolution of the ICM Fe abundance
!
The ICM is already significantly enriched (ZFe~0.25 Z☉) at a lookback time of 9 Gyr.
Mild evolution: <Fe (ICM)> today is ~1.5x larger than at z ~1.2
!
Balestra et al. (2007)
METALLICITY
56 clusters at z= [0.2-1.2],
binned in 5 redshift bins.
!
The dashed line indicates the
best fit over the redshift bins
Z = Z0 (1 + z )−1.25

104. • z~0 Local universe is dominated by CC: 50-70%, tcool e.g. Hudson+2010
!
• z<0.4 No evolution BCS tcool +Temp ratio Bauer+2005
!
• 0.5< z <0.9 Strong evolution, cuspiness parameter Vikhlinin+2007
α = d log (n) / d log (r), r=0.04 r500
!
• 0.7< z <1.4 Moderate evolution: most high-z clusters are moderate CC
cSB = SB < 40 kpc / SB < 400 kpc (core/bulk)
Santos+2008, 2010
!
EVOLUTION OF COOL CORE CLUSTERS
64

105. • z~0 Local universe is dominated by CC: 50-70%, tcool e.g. Hudson+2010
!
• z<0.4 No evolution BCS tcool +Temp ratio Bauer+2005
!
• 0.5< z <0.9 Strong evolution, cuspiness parameter Vikhlinin+2007
α = d log (n) / d log (r), r=0.04 r500
!
• 0.7< z <1.4 Moderate evolution: most high-z clusters are moderate CC
cSB = SB < 40 kpc / SB < 400 kpc (core/bulk)
Santos+2008, 2010
!
EVOLUTION OF COOL CORE CLUSTERS
64

106. • z~0 Local universe is dominated by CC: 50-70%, tcool e.g. Hudson+2010
!
• z<0.4 No evolution BCS tcool +Temp ratio Bauer+2005
!
• 0.5< z <0.9 Strong evolution, cuspiness parameter Vikhlinin+2007
α = d log (n) / d log (r), r=0.04 r500
!
• 0.7< z <1.4 Moderate evolution: most high-z clusters are moderate CC
cSB = SB < 40 kpc / SB < 400 kpc (core/bulk)
Santos+2008, 2010
!
EVOLUTION OF COOL CORE CLUSTERS
64
See also McDonald et al. 2013, mass selected sample from SPT
!
Studies at high-z have important implications to constrain the feedback mechanisms
and AGN duty cycles

107. Feedback in action in WARPJ1415 at z=1
Santos et al. 2012
65
EVOLUTION OF COOL CORE CLUSTERS
First evidence for the existence of cool core clusters at z=1
Radio VLA (res ~ 2”) Residual Chandra -β model
80 kpc
1’ (480 kpc)
Radio VLA (res ~ 2”) Residual Chandra -β model
80 kpc
1’ (480 kpc)
Nuclear emission:
L1.4GHz = 2.0x1025 W/Hz
+ one sided jet/tail feature
Asymmetry in SB:
reg. 1 is 25% less luminous than reg. 2
Radio VLA (res ~ 2”) Residual Chandra -β model
Chandra 370 ksec
~7500 counts

108. Santos et al. 2012
66
EVOLUTION OF COOL CORE CLUSTERS
T drop: 4.6 – 8.0 keV
Fe peak: 3.6-0.9
+1.5 Zsun
2σ detections Si, S, Ni
Mfe
exc=1.8-0.5
+0.7 x109 Msun
T drop 4.6 - 8.0 - 5.7 keV
Z 3.6±1.0 Z
t 0.06±0.01 Gyr
K 9.9±2.0 keVcm
Fe peak in the core suprasolar
➔ short enrichment time ~ 2-3 Gyr

109. 67
A COOLING FLOW ?

110. 67
Cooling-Flow-Induced Starburst in the Core of a Highly Luminous Galaxy Cluster:
Phoenix cluster at z=0.6 SPT-CLJ2344-4243 McDonald +2012,2013
A COOLING FLOW ?
M200 =25 x1014 M☉

111. 67
Cooling-Flow-Induced Starburst in the Core of a Highly Luminous Galaxy Cluster:
Phoenix cluster at z=0.6 SPT-CLJ2344-4243 McDonald +2012,2013
A COOLING FLOW ?
BCG has SFR=740 M☉/yr
M200 =25 x1014 M☉

112. 67
Cooling-Flow-Induced Starburst in the Core of a Highly Luminous Galaxy Cluster:
Phoenix cluster at z=0.6 SPT-CLJ2344-4243 McDonald +2012,2013
A COOLING FLOW ?
cooling rate
BCG has SFR=740 M☉/yr
M200 =25 x1014 M☉

113. EVOLUTIONARYTRENDS
IN GALAXY POPULATIONS

114. EVOLUTION OFTHE BCG
69
Massive BCGs are found out to z~1.4, beyond that they appear to be in a phase of
assembly
(At high-z, there appears to be a higher incidence of X-ray bright AGN coincident with the BCG)

115. !
!
Evolution of BCG size:
ETGs in general are more compact at z > 2 than at z=0
Size of high-z BCGs: controversial results (Huertas-Company 2013)
ranging between little to strong size evolution (up to z~1.3)
BCGs are larger than field galaxies at same M*
⧲ satellites
⧳ BCG
EVOLUTION OFTHE BCG
69
Massive BCGs are found out to z~1.4, beyond that they appear to be in a phase of
assembly
(At high-z, there appears to be a higher incidence of X-ray bright AGN coincident with the BCG)

116. !
!
Evolution of BCG size:
ETGs in general are more compact at z > 2 than at z=0
Size of high-z BCGs: controversial results (Huertas-Company 2013)
ranging between little to strong size evolution (up to z~1.3)
BCGs are larger than field galaxies at same M*
M*of BCGs increases by a factor ~2 from z=0.9 to 0.2.
Most of the mass build up occurs through dry mergers.
Evolution of BCG stellar mass e.g. Lidman et al. 2012
⧲ satellites
⧳ BCG
EVOLUTION OFTHE BCG
69
Massive BCGs are found out to z~1.4, beyond that they appear to be in a phase of
assembly
(At high-z, there appears to be a higher incidence of X-ray bright AGN coincident with the BCG)

117. EVOLUTION OFTHE CMR
zero point
!
!
!
slope
!
!
!
scatter
Mei et al. 2009
No significant evolution
out to redshift z ≈ 1.3 or
significant dependence on
cluster mass
Need HST data (0.1” angular resolution) to obtain accurate photometry
70
MB

118. EVOLUTION - MORPHOLOGY
Evolution of the Morphology-Density relation
!
● Local
+ Distant
At low z: fractions of all morphological types independent of cluster mass
At high z:
- stronger evolution of the spiral + S0 fractions in less massive clusters
- fraction of Ells unchanged.
Poggianti 2009
71
Mcluster =

119. • SFHs in ETGs: cluster vs field
EVOLUTION OF SFHS
Fraction of best fit models for the
field and cluster samples, as a
function of the star-formation
weighted age tSFR
Small but significant difference in the SFHs
of the cluster & field populations:
cluster galaxies form the bulk of their stars
∼0. 5 Gyr earlier than their counterparts in
the field, with massive ETGs having already
finished forming stars at z >1. 5 in both
environments.
Gobat + 2008
RDCS J1252.9-2927 @ z=1.2 vs GOODS
0.5 Gyr

120. • SFHs in ETGs: cluster vs field
EVOLUTION OF SFHS
Fraction of best fit models for the
field and cluster samples, as a
function of the star-formation
weighted age tSFR
Small but significant difference in the SFHs
of the cluster & field populations:
cluster galaxies form the bulk of their stars
∼0. 5 Gyr earlier than their counterparts in
the field, with massive ETGs having already
finished forming stars at z >1. 5 in both
environments.
Gobat + 2008
RDCS J1252.9-2927 @ z=1.2 vs GOODS
The SFHs of local ETGs galaxies:
Field galaxies 1 - 2 Gyr younger than
their counterparts in clusters
Thomas + 2005
0.5 Gyr

121. • SFHs in ETGs: cluster vs field
EVOLUTION OF SFHS
Fraction of best fit models for the
field and cluster samples, as a
function of the star-formation
weighted age tSFR
Small but significant difference in the SFHs
of the cluster & field populations:
cluster galaxies form the bulk of their stars
∼0. 5 Gyr earlier than their counterparts in
the field, with massive ETGs having already
finished forming stars at z >1. 5 in both
environments.
Gobat + 2008
RDCS J1252.9-2927 @ z=1.2 vs GOODS
The SFHs of local ETGs galaxies:
Field galaxies 1 - 2 Gyr younger than
their counterparts in clusters
Thomas + 2005
0.5 Gyr
At higher redshift (z~1.2) differences between the
SFHs of ETGs in clusters and in the field are
smaller than in the local universe

122. Reversal of Star Formation - Density relation: when (z), where (galaxy density) ?
In the local Universe it has been observed that star forming galaxies prefer low galaxy
density environments, i.e., the field relative to clusters, and the cluster outskirts
relative to the core
EVOLUTION OF SFR
73

123. Reversal of Star Formation - Density relation: when (z), where (galaxy density) ?
In the local Universe it has been observed that star forming galaxies prefer low galaxy
density environments, i.e., the field relative to clusters, and the cluster outskirts
relative to the core
Field (low galaxy density) at z=1 Elbaz+ 2007
Results at high-redshift:
EVOLUTION OF SFR
73

124. Reversal of Star Formation - Density relation: when (z), where (galaxy density) ?
In the local Universe it has been observed that star forming galaxies prefer low galaxy
density environments, i.e., the field relative to clusters, and the cluster outskirts
relative to the core
Field (low galaxy density) at z=1 Elbaz+ 2007
Results at high-redshift:
EVOLUTION OF SFR
73

125. Reversal of Star Formation - Density relation: when (z), where (galaxy density) ?
In the local Universe it has been observed that star forming galaxies prefer low galaxy
density environments, i.e., the field relative to clusters, and the cluster outskirts
relative to the core
Galaxy group (intermediate galaxy density)
at z=1.6 Tran+ 2010
Field (low galaxy density) at z=1 Elbaz+ 2007
Results at high-redshift:
EVOLUTION OF SFR
73

126. Reversal of Star Formation - Density relation: when (z), where (galaxy density) ?
In the local Universe it has been observed that star forming galaxies prefer low galaxy
density environments, i.e., the field relative to clusters, and the cluster outskirts
relative to the core
Galaxy group (intermediate galaxy density)
at z=1.6 Tran+ 2010
Field (low galaxy density) at z=1 Elbaz+ 2007
Results at high-redshift:
EVOLUTION OF SFR
73
!
!
!
Galaxy clusters (high galaxy density) ???
!
!

127. EVOLUTION OF SFR
Popular technique: narrow-band imaging of Ha and OII emitters
!
MAHALO: Mapping Hα and Lines of Oxygen with Subaru, PI Kodama
74

128. XCSJ2215, z=1.46, Suprime + NB912 (OII)
Hayashi et al. 2010
RXJ1716, z=0.81, MOIRCS + NB119 (Ha)
Koyama et al. 2010
EVOLUTION OF SFR
75

129. XCSJ2215, z=1.46, Suprime + NB912 (OII)
Hayashi et al. 2010
RXJ1716, z=0.81, MOIRCS + NB119 (Ha)
Koyama et al. 2010
EVOLUTION OF SFR
!
From z=0.8 to z=1.46
increase in #SFGs in core
75

130. EVOLUTION OF SFR PER HALO MASS
Large uncertainty on the evolution of SFR, parametrized as n= 2-7
!
• Studies of massive clusters stop short
of z=1
• Small (cluster) sample statistics
• Lack of spectroscopic information for
galaxy identification
Webb + 2013
76
!
• Optically selected sample, RDCS
• 42 clusters, Spitzer/24um data
• ΣSFR/M ∝ (1+z)5.4

131. EVOLUTION OF SFR PER HALO MASS
!
Evolution of SFR per normalized halo mass: Σ (SFR) / MCLUSTER for groups & massive clusters
!
• Herschel data
• Mostly X-ray selected clusters
Popesso + 2014
77

132. 7878
EVOLUTION OFTHE MAIN-SEQUENCE OF
STAR FORMATION
Elbaz + 2011

133. DISTANT CLUSTERS
(in order of increasing z)

134. THE MOST DISTANT CLUSTERS
XMMUJ 2235.3 - 2033 at z=1.39
Discovered as extended X-ray emission in XMM-Newton data Mullis + 2005
part of the XMM-Newton Distant Cluster Project
ICM properties analyzed with 200 ksec of Chandra Rosati+ 2009
• Very massive system: M200=6x1014 M⨀
• relaxed cluster: regular morphology, indication of a cool core
• high temperatureT=8.6±1.2 keV
• Z = 0.26 ± Zs (6.7 keV Iron line)

135. THE MOST DISTANT CLUSTERS
XMMUJ 2235.3 - 2033 at z=1.39
Discovered as extended X-ray emission in XMM-Newton data Mullis + 2005
part of the XMM-Newton Distant Cluster Project
ICM properties analyzed with 200 ksec of Chandra Rosati+ 2009
• Very massive system: M200=6x1014 M⨀
• relaxed cluster: regular morphology, indication of a cool core
• high temperatureT=8.6±1.2 keV
• Z = 0.26 ± Zs (6.7 keV Iron line)
Rosati + 2009
Galaxy population studied with HST andVLT Strazzullo +2010
• galaxies in the core (< 250 kpc) are very old, massive (1011
M*), red & dead
• prominent BCG, 1 mag brighter than next brightest gal
• strong mean age radial gradient: core galaxies have zf ~5,
whereas galaxies in the outskirts have zf~2

136. 81
• Star formation histories derived with
BC03 models for the sample of
passive galaxies in the core and
outskirts of XMM2235.
Rosati + 2009
Rosati + 2009
THE MOST DISTANT CLUSTERS
XMMUJ 2235.3 - 2033 at z=1.39
core galaxies have zf ~5,
whereas galaxies in the
outskirts have zf~2

137. 81
• Star formation histories derived with
BC03 models for the sample of
passive galaxies in the core and
outskirts of XMM2235.
Rosati + 2009
Rosati + 2009
THE MOST DISTANT CLUSTERS
XMMUJ 2235.3 - 2033 at z=1.39
Strazzullo + 2010
• CMR: tight red-sequence, early-type morphology
core galaxies have zf ~5,
whereas galaxies in the
outskirts have zf~2

138. SPT-CL J 2040-4451 at z=1.478
82
THE MOST DISTANT CLUSTERS
• 15 cluster members confirmed, all of them with
OII emission
• M200;SZ = 5.8 ±1.4 x1014 M☉
• Confirmed members all lie beyond the core (250
kpc)
• SFR from OII uncertain. Individual SFRs < 25 M☉/yr
• mid-IR CMR shows a tight sequence of photo-z
candidates
Bayliss et al. 2013
• The most distant SZE cluster, discovered by SPT
zphot
OII spec

139. • Discovered by the XMM-Newton Distant Cluster Project Santos + 2011
• Deepest Chandra observation of a distant cluster (380 ksec, PITozzi)
• The most massive, distant cluster known: M200=(4.7+1.4
-0.9)x1014 M⨀
• T=6.7 keV
IJKs color image
Tozzi + 2015,ApJ
83
THE MOST DISTANT CLUSTERS
XDCP0044.0-2033 @ Z=1.58
Tentative detection of Fe line

140. 84
Far infrared study using Herschel data
• 13 spec. cluster members 9 with [OII]
• Evidence for merger activity in core, BCG in formation
• 12 spec + zphot members detected by Herschel
THE MOST DISTANT CLUSTERS
XDCP0044.0-2033 @ Z=1.58
Santos + 2015, MNRAS

141. FIR Star formation in XDCP0044
!
Indication for reversal of the SF-density relation:
!
high galaxy density SFR(<250 kpc) ≥ 1900 M⊙/yr
low galaxy density SFR(500< r <1000 kpc) ≥ 200 M⊙/yr
!
!spec only
photoz+spec
85

142. FIR Star formation in XDCP0044
!
Indication for reversal of the SF-density relation:
!
high galaxy density SFR(<250 kpc) ≥ 1900 M⊙/yr
low galaxy density SFR(500< r <1000 kpc) ≥ 200 M⊙/yr
!
!spec only
photoz+spec
!
!SFRA<core= 100x
SFRA<outskirts
!
!
!
85

143. SFR of XDCP0044 @ z=1.6 10x greater than predictions

144. XDCP0044
SFR of XDCP0044 @ z=1.6 10x greater than predictions
Santos et al. 2015
prediction
Popesso et al. 2014

145. CLG0218.3-0510 at z=1.62
87
THE MOST DISTANT CLUSTERS
• Discovered as an overdensity of red galaxies in Spitzer
(Papovich + 2010) & as weak X-ray emission in XMM-
Newton (Tanaka + 2010)
• Group “system”: upper limit ~5-7x1013 M⨀ (Tanaka+ 2010)
• Reversal of the SF-density relation within r<1 Mpc using
MIPS data (Tran + 2010)

146. CLG0218.3-0510 at z=1.62
87
THE MOST DISTANT CLUSTERS
• Discovered as an overdensity of red galaxies in Spitzer
(Papovich + 2010) & as weak X-ray emission in XMM-
Newton (Tanaka + 2010)
• Group “system”: upper limit ~5-7x1013 M⨀ (Tanaka+ 2010)
• Reversal of the SF-density relation within r<1 Mpc using
MIPS data (Tran + 2010)

147. CLG0218.3-0510 at z=1.62
87
THE MOST DISTANT CLUSTERS
• Discovered as an overdensity of red galaxies in Spitzer
(Papovich + 2010) & as weak X-ray emission in XMM-
Newton (Tanaka + 2010)
• Group “system”: upper limit ~5-7x1013 M⨀ (Tanaka+ 2010)
• Reversal of the SF-density relation within r<1 Mpc using
MIPS data (Tran + 2010)
zeropoint & scatter of the
CMR for red–sequence
galaxies imply a formation
epoch of zf= 2. 25 - 2. 45,
the time of the last major
SF episode in the red
galaxies

148. CL J1449+0856 at z=2.0
88
THE MOST DISTANT CLUSTERS
Discovered as an overdensity of infrared galaxies with
[3.6um]-[4.5um]>0 Gobat et al. 2011, 2013
!
HST/WFC3 slit less spectroscopy: first direct spectroscopic
confirmation of quiescent galaxies in a z~2 cluster/group
environment
!
26 cluster members: the power of slit less spec. at high-z!
!
• the core is dominated by passive red galaxies, with ~1 Gyr
though there are star forming galaxies too
• no tight red -sequence
• BCG in formation likely responsible for FIR emission
• central X-ray bright AGN
!

149. CL J1449+0856 at z=2.0
88
THE MOST DISTANT CLUSTERS
Discovered as an overdensity of infrared galaxies with
[3.6um]-[4.5um]>0 Gobat et al. 2011, 2013
!
HST/WFC3 slit less spectroscopy: first direct spectroscopic
confirmation of quiescent galaxies in a z~2 cluster/group
environment
!
26 cluster members: the power of slit less spec. at high-z!
!
• the core is dominated by passive red galaxies, with ~1 Gyr
though there are star forming galaxies too
• no tight red -sequence
• BCG in formation likely responsible for FIR emission
• central X-ray bright AGN
!
Strazzullo et al. 2014
support for an accelerated structural
evolution in high-z dense environments
• galaxy sizes: passive early types are 2-3x
smaller than local counterparts *but* on
average 2x larger than z~2 field galaxies

150. Multi-λ observations & Surveys
of Galaxy Clusters
Joana S. Santos
INAF - Arcetri
Francesco Lucchin School
INAF /Teramo
9-10 December 2014

151. OUTLINE - LECTURE 4
• Cluster detection techniques (X-rays, Optical, IR)
• Proto-cluster detection techniques
• Extragalactic surveys: current and future
prospects
90

152. X-RAYS (e.g.Valtchanov et al. 2001)
!
Wavelet technique (e.g.Vikhlinin et al 1998): convolve an image with a wavelet function
!
!
decompose the original image into a number of wavelet coefficient images, over a set of
scales a.
CLUSTER DETECTIONTECHNIQUES
91
e.g. Gaussian kernel

153. CLUSTER DETECTIONTECHNIQUES
Voronoi-Tessellation & Percolation (Ebeling 1993, Sharf et al.1997):
!
• general method (can also be used in the optical)
• detect structures in a distribution of points (photons) by choosing regions with
enhanced surface density relative to an underlying distribution (Poisson).
!
• Each photon defines a centre of a polygon;
92
!
• SB = 1/areapolygon. Comparing the distribution function
of SB to the one expected from a Poisson distribution,
cells above a given threshold are percolated
(connected to form an object).
!
👎 tendency to link nearby objects, difficult to estimate
size
!
!
X-RAYS (e.g.Valtchanov et al. 2001)

154. Optical / infrared
!
Red-sequence (Gladders &Yee 2000)
Galaxy clusters exhibit a well-defined red sequence of
galaxies. How do you find the RS? Choose a color
appropriate for your redshift regime. Construct color slices
from the data and search for overdensities of galaxies in
these slices.
Once significant overdensities are found, the slice containing
the peak signal for the overdensity gives the cluster
candidate's most probable redshift.
CLUSTER DETECTIONTECHNIQUES
93
color slice

155. Optical / infrared
!
Red-sequence (Gladders &Yee 2000)
Galaxy clusters exhibit a well-defined red sequence of
galaxies. How do you find the RS? Choose a color
appropriate for your redshift regime. Construct color slices
from the data and search for overdensities of galaxies in
these slices.
Once significant overdensities are found, the slice containing
the peak signal for the overdensity gives the cluster
candidate's most probable redshift.
Matched filter (Postman 1996, more recent 3D-MF Milkeraitis 2010)
Clusters show a typical DM mass density profile (e.g. NFW). Galaxies trace the DM.
!
Method: select regions in the sky where the distribution of galaxies corresponds to the
projection of average cluster ρprofile. Specify additional info (e.g. z, galaxy LF)
Matched subfilters enables the extraction of a signal corresponding to the existence of
a cluster.
CLUSTER DETECTIONTECHNIQUES
93
color slice

156. Brodwin et al. wavelet map
Cluster candidates
CLUSTER DETECTIONTECHNIQUES
94
P(z) wavelet (Brodwin et al. 2006)
Construct redshift probability functions, P(z), for
each galaxy.
Generate Probability maps in δz = 0.2 redshift slices.
Perform a wavelet analysis tuned to detect structure
on ~500 kpc scales.

157. Redmapper (Rykoff et al. 2013) red sequence photometric cluster finder
- iteratively self trains a model of R-S galaxies (calibrated with spectroscopic z’s)
- “grow” a cluster centered about every (z-phot) galaxy
- rank galaxies in terms of probability to be the BCG
- once a rich cluster (λ≥5, # R-S galaxies hosted by cluster) is identified the
algorithm computes the cluster photometric redshift
!
Brodwin et al. wavelet map
Cluster candidates
CLUSTER DETECTIONTECHNIQUES
94
P(z) wavelet (Brodwin et al. 2006)
Construct redshift probability functions, P(z), for
each galaxy.
Generate Probability maps in δz = 0.2 redshift slices.
Perform a wavelet analysis tuned to detect structure
on ~500 kpc scales.

158. Optical:Weak lensing (e.g. Umetsu 2010)
!
The deep gravitational potential wells of clusters of
galaxies generate weak shape distortions of the images
of background sources due to differential deflection of
light rays, resulting in a systematic distortion pattern of
background source images around the center of
massive clusters.
Fort & Mellier 1994 projected mass distribution k(θ) of A1689 reconstructed using the
WL shear field measured from a a sample of red bg galaxies
Strong distortion
Giant arcs
Medium
distortion
Arclets
Weak
Distortion
Small ellipses
CLUSTER DETECTIONTECHNIQUES
95
➔ P. Rosati talk

159. Sunyaev - Zel’dovich effect
The SZ effect is a spectral distortion imposed on the 2.7 K CMB radiation when the
microwave photons are scattered by the hot gas (ICM) in galaxy clusters (Inverse Compton
scattering).
credit:Aghanim
CLUSTER DETECTIONTECHNIQUES
96

160. Sunyaev - Zel’dovich effect
The SZ effect is a spectral distortion imposed on the 2.7 K CMB radiation when the
microwave photons are scattered by the hot gas (ICM) in galaxy clusters (Inverse Compton
scattering).
Arnaud et al. 2010
credit:Aghanim
SZ effect Compton parameter y, a measure of the gas pressure integrated along the line-of-
sight, y = (σT/me c2) ∫ Pdl, σT is theThomson cross-section, P = neT
!
The total SZ signal, integrated over the cluster extent, is to the integrated Compton parameter
YSZ,YSZ D2
A = (σT/me c2) ∫ PdV
∝
∝
CLUSTER DETECTIONTECHNIQUES
96

161. Zoom in on 23h field map
Lots of bright point
sources
~15-sigma SZ
cluster detectionThese “large-scale”
fluctuations are primary CMB.
The new era of SZ cluster surveys- credit Benson
A small portion of the SPT survey
2.4deg
(RL AGN)
~8 deg2 field
Clusters are seen as
“shadows” against the CMB
(~1 arcmin resolution)

162. Zoom in on 23h field map
Lots of bright point
sources
~15-sigma SZ
cluster detectionThese “large-scale”
fluctuations are primary CMB.
The new era of SZ cluster surveys- credit Benson
A small portion of the SPT survey
2.4deg
(RL AGN)
~8 deg2 field
SPT-CL J2337-5942 (z=0.78)
Clusters are seen as
“shadows” against the CMB
(~1 arcmin resolution)

163. High-z radio galaxies Miley & De Breuck 2008,Venemans et al. 2007
• Distant radio galaxies are among the largest, most luminous & massive objects in the Universe and
are believed to be powered by accretion of matter onto SMBH in the nuclei of their host galaxies.
• Embedded in giant ionized gas halos surrounded by galaxy overdensities, covering a few Mpc.
• The radio galaxy hosts have clumpy optical morphologies, extreme SFR, and large M*.
• Statistics are consistent with every dominant cluster galaxy having gone through a luminous radio
phase during its evolution.
The Spiderweb proto-cluster
HST image
Miley et al 2006
PROTO-CLUSTER DETECTIONTECHNIQUES
98

164. High-z radio galaxies Miley & De Breuck 2008,Venemans et al. 2007
• Distant radio galaxies are among the largest, most luminous & massive objects in the Universe and
are believed to be powered by accretion of matter onto SMBH in the nuclei of their host galaxies.
• Embedded in giant ionized gas halos surrounded by galaxy overdensities, covering a few Mpc.
• The radio galaxy hosts have clumpy optical morphologies, extreme SFR, and large M*.
• Statistics are consistent with every dominant cluster galaxy having gone through a luminous radio
phase during its evolution.
The Spiderweb proto-cluster
HST image
Miley et al 2006
QSOs at z>4 may also trace
proto-clusters Banados et al. 2013
Motivation, MBH correlate with MDM halo
in nearby galaxies, strong clustering
Detection: look for star-forming galaxies
(Ly-α emission galaxies) around QSOs
Caveat: QSO emission may be a hostile
environment and quench SF.
PROTO-CLUSTER DETECTIONTECHNIQUES
98

165. PLANCK BLOBS - far infrared and sub mm
see work of Dole, Montier, Cacho-Flores, Clemens
Planck color selection: red sources (350um peakers / 500um risers) show Herschel/
SPIRE counterparts (FIR): bright lensed sources OR overdensities of SF galaxies
!
credit: Cacho-Flores
• 5 blobs confirmed at z>1.7
• Promising samples for
high-z studies
• Extensive multi-λ follow-
up on-going
PROTO-CLUSTER DETECTIONTECHNIQUES
99

166. CLUSTERS AS COSMOLOGICAL PROBES
Galaxy clusters are also tracers of the large-scale structure, making them
powerful tools to constrain the cosmological parameters Ωm, σ8 and to a lesser
degree, ΩΛ.
!
Methodologies based on X-ray observations of clusters to constrain cosmological parameters:
!
• The mass function of local clusters, n(M)
• baryon mass fraction, fb
• The gas mass fraction in clusters,fgas
• The evolution of the cluster mass function, n(M,z)
!
!
!
!
!
!
!
100
➔ see B. Sartoris’ talk

167. CLUSTERS AS COSMOLOGICAL PROBES
Galaxy clusters are also tracers of the large-scale structure, making them
powerful tools to constrain the cosmological parameters Ωm, σ8 and to a lesser
degree, ΩΛ.
!
Methodologies based on X-ray observations of clusters to constrain cosmological parameters:
!
• The mass function of local clusters, n(M)
• baryon mass fraction, fb
• The gas mass fraction in clusters,fgas
• The evolution of the cluster mass function, n(M,z)
!
!
!
!
!
!
!
Vikhlinin et al 2009
w0 = −0 .991 ± 0 .045
introducing clusters yields
a factor 2 improvement in
cosmo contraints
100
➔ see B. Sartoris’ talk
5x

168. CLUSTERS AS COSMOLOGICAL PROBES
Galaxy clusters are also tracers of the large-scale structure, making them
powerful tools to constrain the cosmological parameters Ωm, σ8 and to a lesser
degree, ΩΛ.
!
Methodologies based on X-ray observations of clusters to constrain cosmological parameters:
!
• The mass function of local clusters, n(M)
• baryon mass fraction, fb
• The gas mass fraction in clusters,fgas
• The evolution of the cluster mass function, n(M,z)
!
!
!
!
!
!
!
Vikhlinin et al 2009
!
The important quantity to measure (regardless of
the type of observation) is the cluster mass.
!
w0 = −0 .991 ± 0 .045
introducing clusters yields
a factor 2 improvement in
cosmo contraints
100
➔ see B. Sartoris’ talk
5x

169. MEASURING CLUSTER MASSES
!
Dynamical analysis from galaxy kinematics: Cluster velocity dispersion
M = 3 σ2 R/G
Richness: N200 , number of red-sequence galaxies within a scaled radius such
the <ρgalaxy(<r)> is 200x ρcrit U : N200 ~ 10 - 100 Rozo et al. 2012
Weak & strong lensing: measure of the shapes of background galaxies and
compare them with the expectations for an isotropic distribution of galaxies
( e.g. Umetsu 2011)
X-ray: Scaling relations: LX - M ,TX - M,Yx - M
!
!
Sunyaev - Zel’dovich effect:
101
X-rays: Hydrostatic equilibrium
➔ see B. Sartoris’ & P. Rosati’s talks

170. MEASURING CLUSTER MASSES
Cluster mass under the hypothesis of Hydrostatic Equilibrium (HE)
HE determines the balance between the pressure and the gravitational forces:
∇Pgas = - ρgas ∇ ϕ
!
102

171. MEASURING CLUSTER MASSES
Cluster mass under the hypothesis of Hydrostatic Equilibrium (HE)
HE determines the balance between the pressure and the gravitational forces:
∇Pgas = - ρgas ∇ ϕ
!
102
assume spherically symmetric gas distribution & equation of state of ideal gas
➔

172. MEASURING CLUSTER MASSES
Cluster mass under the hypothesis of Hydrostatic Equilibrium (HE)
HE determines the balance between the pressure and the gravitational forces:
∇Pgas = - ρgas ∇ ϕ
!
102
assume spherically symmetric gas distribution & equation of state of ideal gas
➔
* mp is the proton mass and µ is the mean molecular weight

173. MEASURING CLUSTER MASSES
Cluster mass under the hypothesis of Hydrostatic Equilibrium (HE)
HE determines the balance between the pressure and the gravitational forces:
∇Pgas = - ρgas ∇ ϕ
!
102
assume spherically symmetric gas distribution & equation of state of ideal gas
➔
* mp is the proton mass and µ is the mean molecular weight

174. MEASURING CLUSTER MASSES
Cluster mass under the hypothesis of Hydrostatic Equilibrium (HE)
HE determines the balance between the pressure and the gravitational forces:
∇Pgas = - ρgas ∇ ϕ
!
102
assume spherically symmetric gas distribution & equation of state of ideal gas
➔
* mp is the proton mass and µ is the mean molecular weight

175. MEASURING CLUSTER MASSES
Cluster mass under the hypothesis of Hydrostatic Equilibrium (HE)
HE determines the balance between the pressure and the gravitational forces:
∇Pgas = - ρgas ∇ ϕ
!
102
assume spherically symmetric gas distribution & equation of state of ideal gas
➔
* mp is the proton mass and µ is the mean molecular weight

176. X-RAYS INFRARED W-LENSING SZ
REFLEX SPARCS LOCUSS SPT
REXCESS GCLASS CLASH ACT
400 SD IDCS LSST
XDCP ISCS EUCLID
XXL (ON-GOING) MADCOWS
IMPORTANT CLUSTER SAMPLES

177. X-RAYS INFRARED W-LENSING SZ
REFLEX SPARCS LOCUSS SPT
REXCESS GCLASS CLASH ACT
400 SD IDCS LSST
XDCP ISCS EUCLID
XXL (ON-GOING) MADCOWS
Rosat
IMPORTANT CLUSTER SAMPLES

178. X-RAYS INFRARED W-LENSING SZ
REFLEX SPARCS LOCUSS SPT
REXCESS GCLASS CLASH ACT
400 SD IDCS LSST
XDCP ISCS EUCLID
XXL (ON-GOING) MADCOWS
Rosat
XMM-Newton
IMPORTANT CLUSTER SAMPLES

179. X-RAYS INFRARED W-LENSING SZ
REFLEX SPARCS LOCUSS SPT
REXCESS GCLASS CLASH ACT
400 SD IDCS LSST
XDCP ISCS EUCLID
XXL (ON-GOING) MADCOWS
Rosat
XMM-Newton
Spitzer/IRAC
IMPORTANT CLUSTER SAMPLES

180. X-RAYS INFRARED W-LENSING SZ
REFLEX SPARCS LOCUSS SPT
REXCESS GCLASS CLASH ACT
400 SD IDCS LSST
XDCP ISCS EUCLID
XXL (ON-GOING) MADCOWS
Rosat
XMM-Newton WISE
Spitzer/IRAC
IMPORTANT CLUSTER SAMPLES

181. EXTRAGALACTIC SURVEYS
• Planck sub-mm, radio
• SPT & ACT SZE
• eROSITA X-ray
• DES: Dark Energy Survey
• Euclid optical/NIR
• LSST NIR
104

182. PLANCK
!
• ESA mission w/ NASA involvement (2013)
• Instruments: HFI (83 - 857 GHz) & LFI (27 - 77 GHz)
!
• Primary science goals:
• Mapping the CMB anisotropies with improved sensitivity and angular resolution
• Measuring the amplitude of structures in the CMB
• Perform measurements of Sunyaev-Zel'dovich effect
microwave radio
http://sci.esa.int/planck/53104-cosmic-structure/
105

183. PLANCK
!
• ESA mission w/ NASA involvement (2013)
• Instruments: HFI (83 - 857 GHz) & LFI (27 - 77 GHz)
!
• Primary science goals:
• Mapping the CMB anisotropies with improved sensitivity and angular resolution
• Measuring the amplitude of structures in the CMB
• Perform measurements of Sunyaev-Zel'dovich effect
microwave radio
Clusters:
Planck catalogue of SZE sources, Planck 2013 results. XXIX, arXiv:1303.5089
861 confirmed clusters: 683 are previously-known, 178 are newly confirmed, 366 are
candidates
Planck clusters under-luminous for their masses, 70% new clusters have disturbed
morphologies
http://www.sciops.esa.int/index.php?project=PLANCK&page=Planck_Published_Papers
http://sci.esa.int/planck/53104-cosmic-structure/
105

184. The SPT experiment consists of three completed, underway, or planned surveys:
1) SPT-SZ (2007-2011) with 2500 deg2, 1k detectors
2) SPTpol (2012-2015) 1600 detectors
3) SPT-3G (2016-2019) 15k detectors
The SPT-SZ survey has provided a new catalog of approximately 500 of the most
massive, distant clusters in the universe, about 75% of which are new discoveries.
Benson et al 2013
SOUTH POLETELESCOPE
credit: Google images
10-meter telescope
operating in the mm-
wavelength, optimized for
low-noise measurements
of the CMB
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185. “El Gordo” z=0.9, M=1015 M⊙ (Menanteau 2012)
ATACAMA COSMOLOGYTELESCOPE
The Atacama CosmologyTelescope (ACT) is a
custom 6-meter telescope in Chile.
ACT observes simultaneously in 3 frequency
bands centered on 148 GHz, 218 GHz, and
277 GHz
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186. DARK ENERGY SURVEY
!
• DES began in Sept. 2013 and will continue for 5 years. It will map 1/8th of
the sky (5000 deg) in unprecedented detail.
• Goal: investigate the nature of Dark Energy by combining SN Ia, BAO,
Galaxy Clusters and Weak Lensing.
• Science for clusters: 100,000 galaxy clusters expected
Galaxy Cluster counts (red - sequence technique)
Gravitational lensing
Optical survey (5 filters) using the DECam camera (2.2 deg2 FOV)
mounted on the 4-m Blanco telescope. 25 institutions in 6 countries
/wiki/The_Dark_Energy_Survey
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187. EUCLID!
ESA Cosmic Vision http://sci.esa.int/euclid/
Euclid is an ESA mission to map the geometry of the dark Universe.
The mission will investigate the distance-redshift relationship and
the evolution of cosmic structures by measuring shapes and
redshifts of galaxies and clusters of galaxies out to redshifts ~2
(look-back time of 10 billion years). Start: 2020
Euclid is optimised for two primary cosmological probes:
!
• Weak gravitational Lensing (WL):Weak lensing is a method to map the dark matter and
measure dark energy by measuring the distortions of galaxy images by mass
inhomogeneities along the line-of-sight.
• Baryonic Acoustic Oscillations (BAO): BAOs are wiggle patterns, imprinted in the
clustering of galaxies, which provide a standard ruler to measure dark energy and the
expansion in the Universe.
!
★ One optical broad band (imaging) + 3 NIR bands (imaging + grisms)
★ Target: star-forming galaxies from z~1-2.Will detect all clusters up to the proto-cluster regime
(z>2).
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188. LSST
• 8-m telescope in Chile with a FOV of 9.6 ▢ deg, that will repeatedly scan the sky south of
+10 deg DEC accumulating 1000 pairs of 15 second exposures through ugrizy filters
• will yield the main 20,000 ▢ degree deep-wide-fast survey (depth r ~24.5)
• First light planned for 2022
!
Main Scientific goal of the LSST: probe the physics of DE
Probes: weak lensing (WL), baryon acoustic oscillations (BAO), SN Ia, and cluster counts.
Combination of probes can yield the precision to distinguish between models of dark energy.
By simultaneously measuring mass growth (via WL + cluster counting) and curvature (via
BAO and SN), LSST data will tell us whether the recent cosmic acceleration is due to dark
energy or modified gravity.
The power and accuracy of LSST dark energy and dark matter probes is derived from samples of
several billion galaxies and tens of millions of Type-I supernovae.
Large Synoptic SurveyTelescope
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189. EROSITA
http://www.mpe.mpg.de/eROSITA
Goal: detect the hot intergalactic medium of
50-100 thousand galaxy clusters and groups and
hot gas in filaments between clusters to map
out the large scale structure in the Universe for
the study of cosmic structure evolution
• eROSITA: primary instrument on-board the
Russian "Spectrum-Roentgen-Gamma" (SRG)
satellite will be launched from Baikonur in 2015
(L2 orbit).
• First imaging all-sky survey in the medium energy
X-ray range up to 10 keV with an unprecedented
spectral and angular resolution.
• Telescope: 7 identical Wolter-1 mirror modules.
Each module contains 54 nested mirror shells.
Novel detector system based on the XMM-
Newton pn-CCD technology.
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190. EROSITA
112

191. FUTURE CHALLENGES & OPPORTUNITIES
• Multi-wavelength is the way!
• Bridging the gap between massive clusters and proto-
clusters
• Evolution of star-formation in clusters
• Evolution and “onset” of metals in the ICM
• Invest in assembling large, *representative* cluster samples
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192. ADDITIONAL INFORMATION…
• European charter and code for researchers:
http://ec.europa.eu/euraxess/index.cfm/rights/europeanCharter
• EURAXESS portal: http://ec.europa.eu/euraxess/
• EURODOC: http://www.eurodoc.net/
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