(cosmologywith) x-rayclusterstudiescosmicmaps.uchicago.edu/depot/a-vikhlinin.pdf · 3....
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( Cosmology with )X-ray cluster studies
Alexey Vikhlinin
X-ray image (Bootes region survey)
∼ 3 − 4 per deg2 ... z = 0 − 1.5 ... very clean samples
Basic results from ROSAT
samples of a few 100’s clusters at z ≈ 0 and a few 10’s at z ≈ 0.5
Future Projects
eROSITA on SRG (Russia + Germany)
« - »
3.
eROSITA
Lobster
ART-XC
30
. 3.1.1 eROSITA, ART-XC Lobster « ». « »
, 30, .
« » .
. 3.1.1 :
eROSITA (MPE, ) Wolter-I, 7 , – 35 ,
0.2-12 , ~20 () ~15 , 130 6 ,
2500 2, grasp - S ~700 2 2 1 ,
600 , 95 , 1.3 2.6 ;
ART-XC – Astronomical Roentgen Telescope - X-ray Concentrator ( ,), 6 - , 5-80 , 46 5 3 80 ,
103 2 30 , S 150 2 2 10 ,150 6 1 60 ,
300 , – 160 (TBC);
WFXT (US; mission concept study proposed)
4 Will nd ALL clusters in the Universe withM > 2 × 1014 h−1M⊙ (T > 4 keV)
4 > 100, 000 clusters in all sky
4 Populate knots of cosmic web
“Observers are insuciently smart”
Rely on Lx ∼ Mα
Fit cosmology and L −M
+ clustering + shape of dN/dL
0.7
-0.9
-0.8
-0.7
0
1
2
0.72 0.74
ΩΛ ΩΛ ΩΛ
w
0.60.5 0.7 0.8 0.9 0.60.5 0.7 0.8 0.9
power law
cubic σ2lnM
fixed
free
0
1
2(a) Clustering (b) Shape (c) Clustering+Shape
“Theorists are too smart for their own good”
Use betterM estimators, rely less on modeling
10 100 100010−7
10−6
10−5
10−4
10−3
10−2
10−1
r, kpc
∫ n2d
l,10
66cm
−5
r500r2500
Mtot = −r2
G∇Pgρg
∝ T(r) r (d ln ρgd ln r
+ d lnTd ln r
)
Role of simulations
Calibration of dn/dM Identify robust Mtot proxies Calibrate observational biases via mock data analysis First-order corrections toMtot vs. proxy relations.
papers by Kravtsov, Nagai & AV
Proxies: YX = TX ×Mgas, X
Expected: M ∝ Y3/5X E(z)−2/5 — virial theorem + self-similarity + “fair sample”
Are simulations realistic?
Are simulations realistic?
Nagai, Kravtsov, Vikhlinin ’07
Observational calibration of M–YX
1013 1014 1015
1014
1015
M5
00
E(z
)2/
5,h
1/
2M
⊙
YX , M⊙ keV
— Chandra; — lensing from Hoekstra ’07
Comparison of X-ray and optical masses
Churazov etal ’07 (astro-ph)
Samples for cosmological work
41 at z > 0.35 from 400d http://hea-www.harvard.edu/400d
48 at z ∼ 0.05 − 0.15 from ROSAT All-Sky Survey (Chandra archive)
0.0 0.5 1.0
1
10
100
z
Npe
r∆
z=
0.05
Volume = 3 ×V(z < 0.1)
Role of d(z) and H(z) in mass function test
Cluster mass functions
z = 0.025 − 0.25
z = 0.40 − 0.90
ΩM = 0.25 ΩΛ = 0.75 h = 0.7
1014 101510−10
10−9
10−8
10−7
10−6
10−5
M324, h−1 M
N(>
M),
h−3
Mpc−3
Cluster mass functions
z = 0.025 − 0.25
z = 0.40 − 0.90
ΩM = 0.25 ΩΛ = 0 h = 0.7
1014 101510−10
10−9
10−8
10−7
10−6
10−5
M324, h−1 M⊙
N(>
M),
h−3
Mpc−3
σ8 constraints
Dark energy data
Dark energy: pX = w ρx ; curvature: Ωk ≡ 1 −ΩM −ΩX ≠ 0
Data: WMAP-3
clusters
SN Iapeaks in P(k)
z = 0.025 − 0.25
z = 0.40 − 0.90
ΩM = 0.25 ΩΛ = 0.75 h = 0.7
1014 101510−10
10−9
10−8
10−7
10−6
10−5
M324, h−1 M
N(>
M),
h−3
Mpc−3
Dark energy data
Dark energy: pX = w ρx ; curvature: Ωk ≡ 1 −ΩM −ΩX ≠ 0
Data: WMAP-3
clusters
SN Iapeaks in P(k)
z = 0.025 − 0.25
z = 0.40 − 0.90
ΩM = 0.25 ΩΛ = 0.75 h = 0.7
1014 101510−10
10−9
10−8
10−7
10−6
10−5
M324, h−1 M
N(>
M),
h−3
Mpc−3
σ8 ∝ δζ (Ωbh2)−1/3 (ΩMh2)0.563 h0.693G0
Flatclusters + CMB
0.20 0.25 0.30 0.35
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
ΩM
w
SN Ia + CMB
0.20 0.25 0.30 0.35
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
ΩM
w
SDSS & 2dF + CMB
0.20 0.25 0.30 0.35
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
ΩM
w
Non-atclusters + CMB
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
SN Ia + CMB
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
SDSS & 2dF + CMB
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
Flat SN Ia + CMB + SDSS & 2dF + clusters
0.20 0.25 0.30 0.35
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
ΩM
w
Non-atSN Ia + CMB + SDSS & 2dF + clusters
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
χ2CMB= 1.2 / 2dofχ2BAO= 0.2 / 1dofχ2σ8 = 2.2 / 1dofχ2evol = 3.1 / 3dofχ2P(k)= 2.1 / 1dofχ2SN = 0.1 / 1dof
χ2tot = 8.9 / 9dof
w = −1.06 ± 0.07ΩM = 0.28 ± 0.02Ωk = −0.005 ± 0.02
σ8 = 0.78, h = 0.69
z = 0.025 − 0.25
z = 0.40 − 0.90
ΩM = 0.25 ΩΛ = 0.75 h = 0.7
1014 101510−10
10−9
10−8
10−7
10−6
10−5
M324, h−1 M
N(>
M),
h−3
Mpc−3
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
Flat clusters + CMB + SDSS & 2dF
0.20 0.25 0.30 0.35
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
ΩM
w
SN Ia + CMB + SDSS & 2dF
0.20 0.25 0.30 0.35
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
ΩM
w
Non-atclusters + CMB + SDSS & 2dF
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
SN Ia + CMB + SDSS & 2dF
−0.15 −0.10 −0.05 0.00 0.05 0.10 0.15
−1.20
−1.10
−1.00
−0.90
−0.80
−0.70
−0.60
−0.50
Ωk
w
“Trivial highlights”
Cluster evolution “detects Λ”:
z = 0.025 − 0.25
z = 0.40 − 0.90
ΩM = 0.25 ΩΛ = 0 h = 0.7
1014 101510−10
10−9
10−8
10−7
10−6
10−5
M324, h−1 M⊙
N(>
M),
h−3
Mpc−3
“Trivial highlights”
Cluster evolution “detects Λ”. gives good σ8:
“Trivial highlights”
Cluster evolution “detects Λ”. gives good σ8. inconsistent with ΩM = 1:
“Trivial highlights”
Cluster evolution “detects Λ”. gives good σ8. inconsistent with ΩM = 1:
Luminosity-Mass relation
ln Lx = B + A lnM + α E(z) ± σ
A = 1.60
α = 1.855
σ = 0.40
M87
“Bullet Cluster”
“Bullet Cluster”
ΩM −ΩΛ constraints
Cluster evolution + Shape of N(M)
0.0 0.2 0.4 0.6 0.8 1.00.0
0.2
0.4
0.6
0.8
1.0
ΩM
ΩΛ