Mapping Hot Gas in the Universe using the Sunyaev-Zeldovich Effect

Mapping Hot Gas in the Universe using the

Sunyaev-Zeldovich Effect

Eiichiro Komatsu (Max-Planck-Institut für Astrophysik) Cosmology Group Seminar, ETH Zürich

June 7, 2018

Where is a galaxy cluster?

Subaru image of RXJ1347-1145 (Medezinski et al. 2010) http://wise-obs.tau.ac.il/~elinor/clusters

2

Where is a galaxy cluster?

Subaru image of RXJ1347-1145 (Medezinski et al. 2010) http://wise-obs.tau.ac.il/~elinor/clusters

3

Subaru image of RXJ1347-1145 (Medezinski et al. 2010) http://wise-obs.tau.ac.il/~elinor/clusters

Subaru

4

Hubble image of RXJ1347-1145 (Bradac et al. 2008)

Hubble

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Chandra X-ray image of RXJ1347-1145 (Johnson et al. 2012)

Chandra

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Chandra X-ray image of RXJ1347-1145 (Johnson et al. 2012)

ALMA Band-3 Image of the

Sunyaev-Zel’dovich effect at 92 GHz (Kitayama et al. 2016)

ALMA!

5” resolution

7

1σ=17 μJy/beam

=120 μKCMB

T. Kitayama

A clear displacement between

the X-ray and SZ images. What is going on?

8

9

Multi-wavelength Data

Optical:

•10^2–3 galaxies

•velocity dispersion

•gravitational lensing

X-ray:

•hot gas (10^7–8 K)

•spectroscopic TX

•Intensity ~ ne2L

I_X = Z

dl n²_e⇤(T_X)

SZ [microwave]:

•hot gas (10^7-8 K)

•electron pressure

•Intensity ~ neTeL

I_SZ = g_⌫ ^T k_B m_ec²

Z

dl n_eT_e

A Story about RXJ1347–1145

• Let me tell you a little story about this particular

cluster, which highlights the unique power of the SZ data to study cluster astrophysics

• A massive cluster with 10¹⁵ Msun at z=0.45

• The most X-ray luminous galaxy cluster found in the ROSAT All Sky Survey

• Very compact, “cool core” cluster

11

1997

ROSAT/HRI image [Schindler et al.]

5” resolution

• 0.1–2.4 keV

• Looked pretty

“spherical”

• Thought to be a typical, relaxed,

cooling-flow cluster

12

Chandra X-ray image of RXJ1347-1145 (Johnson et al. 2012)

2001

SZ w/ Nobeyama [Komatsu et al.]

12” resolution

• The highest

angular resolution SZ mapping at

that time

• (The record holder for a decade)

• A surprise!

Chandra X-ray image of RXJ1347-1145 (Johnson et al. 2012)

2001

SZ w/ Nobeyama [Komatsu et al.]

12” resolution

• The highest

angular resolution SZ mapping at

that time

• (The record holder for a decade)

• A surprise!

2002

X-ray w/ Chandra [Allen et al.]

• 0.5–7 keV

• An excess X-ray emission found at the location of the SZ excess

• A hot gas, missed by ROSAT due to the lack of

sensitivity at high energies!

A lesson learned

• X-ray observations are band-limited

• They are not usually not sensitive to very hot gas with temperature >10(1+z) keV

• SZ observations are not band-limited

• They are in principle sensitive to arbitrarily high temperatures (more precisely, pressure)

• SZ data probe electron pressure: a good probe of shock-heated gas due to mergers

• RXJ1347–1145 was thought to be a relaxed cluster.

Our Nobeyama data challenged it, and now it is

accepted that this cluster is a merging system! ¹⁶

We have ALMA. Now what?

• What is a new science we can do with such high resolution, high sensitivity measurements?

• Finding shocks and hot clumps is fun, but can we do something new and more quantitative?

• One example: Pressure fluctuations

17

SZ X-ray

Let’s subtract a smooth component

Let’s subtract a smooth component

SZ X-ray

Ueda et al., submitted

Let’s subtract a smooth component

SZ X-ray

Gas density is stirred

(“sloshed”), but no change in pressure! Not sound waves

=> Unique measurements of the effective equation of state of

density fluctuations

Ueda et al., submitted

Overlaid with strong lensing…

Ueda et al., submitted

SZ X-ray

Overlaid with strong lensing…

Ueda et al., submitted

SZ X-ray

Gas stripping?

Full-sky Thermal Pressure Map

North Galactic Pole South Galactic Pole

Planck Collaboration ²³

We can simulate this

arXiv:1509.05134

• Volume: (896 Mpc/h)³

• Cosmological hydro (P-GADGET3) with star formation and AGN feed back

• 2 x 1526³ particles (mDM=7.5x10⁸ Msun/h)

[MNRAS, 463, 1797 (2016)]

24

Klaus Dolag (MPA/LMU)

…like Alex has done it before!

…like Alex has done it before!

Dolag, EK, Sunyaev (2016)

27

• “The local universe simulation” reproduces the observed structures pretty well 28

1-point PDF fits!!

Dolag, EK, Sunyaev (2016)

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Power spectrum fits!!

provided that we use:

⌦

= 0.308

8

= 0.8149

Dolag, EK, Sunyaev (2016)

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Simple Interpretation

• Randomly-distributed point sources

= Poisson spectrum = ∑i(fluxi)² / 4π

multipole Cl [not “l2 Cl”]

31

Simple Interpretation

• Extended sources = the power

spectrum reflects intensity profiles

multipole Cl [not “l2 Cl”]

32

Multipole l(l+1)C l /2 π [ μ K 2 ]

>2x10¹⁵ Msun

>10¹⁵ Msun

>5x10¹⁴ Msun

>5x10¹³ Msun

Adding smaller clusters

33

Simple Formula

• yl with small l just gives the total thermal pressure, MT ~ M^5/3

• Heavily weighted by massive clusters

• The mass function, dn/dM, is sensitive to the amplitude of fluctuations, σ8

C _` =

Z

dz dV dz

Z

dM dn

dM | y _` (M, z ) | ²

2d Fourier transform of pressure

34

Komatsu & Kitayama (1999)

Degree-scale SZ power spectrum

is less sensitive to astrophysics in cluster cores

1999

35

McCarthy et al. (2014)

2014

confirmed by simulations with

varying AGN feedback

36

It is very sensitive to the amplitude of fluctuations

Komatsu & Kitayama (1999) Komatsu & Seljak (2002)

1999

37

McCarthy et al. (2014)

tension?

Planck13 parameters

2014

38

McCarthy et al. (2014)

Planck13 parameters

similar to planck15

2014

39

C _` / ⌦ ³ _{m 8} ⁸

⌦

= 0.308

8

= 0.8149

⌦

= 0.315

8

= 0.829

vs Dolag, EK, Sunyaev (2016)

40

C _` / ⌦ ³ _{m 8} ⁸

⌦

= 0.308

8

= 0.8149

⌦

= 0.315

8

= 0.829

vs Dolag, EK, Sunyaev (2016)

~20% too large

41

Closer look at the measurements

• The compton-Y power spectrum of Planck contains various

foreground sources

• What you saw as the data points were the raw data minus the best- fitting foreground components

• When fitting, the Planck team used Gaussian covariance

ignoring the non-Gaussian term

• How does this affect the results?

Bolliet, Comis, EK, Macias-Perez (2017)

with non-Gaussian error without

42

B. Bolliet

tSZ power slightly lower

Bolliet, Comis, EK, Macias-Perez (2017)

with

non-Gaussian error

without

43

Closer look at the

parameter dependence

Bolliet, Comis, EK, Macias-Perez (2017)

Mass Bias

Hubble σ8

Ωm w ns

44

Closer look at the

parameter dependence

Bolliet, Comis, EK, Macias-Perez (2017)

2.6% measurement!

Essentially cosmological

model-independent

Closer look at the

parameter dependence

Bolliet, Comis, EK, Macias-Perez (2017)

2.6% measurement!

Essentially cosmological

model-independent

Planck Mass Bias

• The key ingredient of the power spectrum is a profile of thermal pressure of electrons

C _` =

Z

dz dV dz

Z

dM dn

dM | y _` (M, z ) | ²

M ˜ _500c = M _500c,true /B

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Mass Bias in ΛCDM

• Constraining the ΛCDM parameters by the Planck (TT+lowP+lensing) chain, we find

• B = 1.54 ± 0.098 (68%CL; Makiya, Ando & EK, arXiv:1804.05008)

• or, 1–b = 0.649 ± 0.041

• Cf: Simulation by Dolag, EK & Sunyaev: B ~ 1.2.

Manifestation that the new Compton-Y power spectrum is lower

48

Towards “Tomography”

• Cross-correlating the Compton-Y map with galaxies with known redshifts!

49

2MASS Redshift Survey

• ~40K galaxies with the median redshift of 0.02

Huchra et al. (2012)

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2MASS Redshift Survey

• ~40K galaxies with the median redshift of 0.02

Huchra et al. (2012)

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2MRS Auto Power

Dominated by 1-halo term in most of the angular scales => Good for cross-correlation with Compton-Y

Ando, Benoit-Levy & EK (2018)

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2MRS Auto Power

Ando, Benoit-Levy & EK (2018)

53

Cross-power!

54

R. Makiya

Mass-bias Consistency

We get consistent mass bias from Compton-Y and 2MRS cross. Neat.

[for Planck TT+lowP+lensing]

55

Makiya, Ando & EK (2018)

Mass Dependence

56

Makiya, Ando & EK (2018)

Mass Dependence

Cross is sensitive to less massive halos: We can use this to explore the mass bias as a function of mass!

57

Makiya, Ando & EK (2018)

Planck Mass Bias

• The key ingredient of the power spectrum is a profile of thermal pressure of electrons

C _` =

Z

dz dV dz

Z

dM dn

dM | y _` (M, z ) | ²

M ˜ _500c = M _500c,true /B

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——

α

58

Mass Dependence Nailed

Makiya, Ando & EK (2018)

59

Redshift Dependence

60

Makiya, Ando & EK (2018)

Redshift Dependence

High-ell data of Compton-Y auto is the key.

But…

foreground contamination

61

Makiya, Ando & EK (2018)

Z-dependence Poorly Constrained

62

Makiya, Ando & EK (2018)

Summary

• New results on the SZ effect, from small to large:

1. The first SZ image by ALMA - opening up a new study of cluster astrophysics via pressure

fluctuations

2. The SZ power spectrum at l<1000 has been determined finally! And we can simulate it

3. Detailed look at mass bias from the SZ power spectrum and cross-correlation tomography

• B = 1.5 ± 0.1 (68%CL) for Planck

TT+lowP+lensing. Expect B ~ 1.2 for hydrostatic mass bias in the simulation. Origin?

B. Bolliet T. Kitayama

K. Dolag

R. Makiya ⁶³

Near Future?

CCAT-p!

Frank’s slide from the Florence meeting

Cornell U. + German consortium + Canadian consortium + …

Frank’s slide from the Florence meeting

A Game Changer

• ^CCAT-p

• Germany makes great telescopes!

•

•

significant contributions towards the CMB S-4 landscape (both US and Europe) by providing telescope designs and the “lessons learned” with prototypes.

CCAT-p Collaboration

CCAT-p Collaboration

Simons Observatory (USA)

in collaboration

South Pole?

Simons Observatory (USA)

in collaboration

South Pole?

This could be

“CMB-S4”

Compton Y Map of RXJ1347–1145

ALMA

on-source integration times 5.6 hours with 7-m array 2.6 hours with 12-m array

Thank you TAC!