SZ effects by using SZ effects by using high-resolution simulationshigh-resolution simulations

Lauro MoscardiniLauro MoscardiniDipartimento di AstronomiaDipartimento di Astronomia

Università di Bologna, ItalyUniversità di Bologna, Italy

lauro.moscardini@unibo.itlauro.moscardini@unibo.it

Orsay, Paris, 7-8th april 2005

Works in collaboration with:Works in collaboration with: S. Borgani,S. Borgani, A. Diaferio, K. Dolag,A. Diaferio, K. Dolag, G. G. Murante,Murante, M. Roncarelli,M. Roncarelli, V. Springel, G. Tormen, L. Tornatore, P. V. Springel, G. Tormen, L. Tornatore, P. Tozzi.Tozzi.Mainly based onMainly based on Diaferio et al. 2005,Diaferio et al. 2005, MNRAS, 356, 1477; MNRAS, 356, 1477; Roncarelli Roncarelli et al. 2005,et al. 2005, in preparation; in preparation; Bonaldi et al.Bonaldi et al. 2005, in preparation 2005, in preparation

A Tree+SPH high-res. Simulation of the cosmic webA Tree+SPH high-res. Simulation of the cosmic web

KP Collaboration: S. Borgani, A. Diaferio, K. Dolag, L. Moscardini, G. Murante, V. Springel, G. Tormen, L.Tornatore, P.Tozzi

L = 192 h-1 Mpc ; Ngas

=NDM

= 4803

Pl

= 7.5 h-1 kpc ; mgas

= 6.9 108 h-1 M⊙

40,000 CPU hours and 100 Gb RAM, using 64 processors of IBM-SP4 in CINECA (INAF grant); about 1.2 Tb of data produced.

Code: Tree + SPH GADGET (Springel et al. 2001, 2002)

www.MPA-Garching.MPG.DE/gadget

Radiative cool.+UV backgr. Multiphase model for star-formation and model galactic winds.

CDM cosmology: m= 1-0.3 ,

bar0.02h-2 , h=0.7 ,

8=0.8

Co-workers: M. Arnaboldi, L.M. Cheng, S. Ettori, O. Gerhard, E. Rasia, M. Roncarelli, plus other students

400400 clusters with clusters with > 10> 1044 particles.particles.X-ray cluster scaling X-ray cluster scaling propertiesproperties and nature and nature of their scatter.of their scatter.Contribution of diffuse Contribution of diffuse gas to the gas to the soft X-ray soft X-ray backgroundbackground..SZ effectSZ effect from from clumped and diffuse gas.clumped and diffuse gas.Comparing cluster Comparing cluster masses:masses: X-ray, lensing, X-ray, lensing, optical and SZ.optical and SZ.DiffuseDiffuseintracluster intracluster light light on a statistical basis.on a statistical basis.oom-in simulations oom-in simulations of clusters and other of clusters and other interesting regions.interesting regions.Populate the box with Populate the box with simulated & SAM galaxies simulated & SAM galaxies

Systematics in the measurements Systematics in the measurements of cluster peculiar velocitiesof cluster peculiar velocities

Question:Question:

How well can we measure the peculiar

velocity of clusters combining

the Sunyaev-Zel’dovich effects?

See Diaferio et al. 2005, MNRAS, 356, 1477See Diaferio et al. 2005, MNRAS, 356, 1477

The cluster sampleThe cluster sample117 clusters @ z=0, with Mvir>1014 Msun

Pixel size 42 kpc/h

No Systematics from velocityNo Systematics from velocity

(i) Is the gas bulk velocity equivalent to the DM bulk velocity?

(ii) What is the average effect of the internal bulk velocity?

Mean absolute deviation: 18 km/sUncertainty smaller than

200 km/s at 93% level

Electronic vs. X-ray temperatureElectronic vs. X-ray temperature

Te = a + b Tx

Are X-ray temperature equivalent to electronic number density?

Answer:

Only in the cluster internal parts (rlim

<0.1 Rvir).

In spatially poorly resolved clusters, using TX rather Te can substantially overestimate the peculiar velocity.

Estimated vs. actual velocitiesEstimated vs. actual velocities

resolved resolved

clustersclusters

unresolved unresolved

clustersclusters

X-ray Temp. electronic Temp.

Scaling relations:Scaling relations:(i) central Compton param. vs. X-ray Luminosity(i) central Compton param. vs. X-ray Luminosity

self-similar expectation: yself-similar expectation: y00 L Lxx3/43/4 E E1/41/4(z)(z)

Simulated clusters: slope (0.79 0.02)

Real clusters:

Open: Mc Carthy et al. (2003)

slope (0.65 0.04)

Solid: Cooray (1999)

slope (0.47 0.07)

Discrepancy between datasets!

Scaling relations:Scaling relations:(ii) central Compton param. vs. X-ray temperature(ii) central Compton param. vs. X-ray temperature

self-similar expectation: yself-similar expectation: y00 T Txx3/23/2 E(z) E(z)

Simulated clusters: slope (1.55 0.03)

Real clusters:

Mc Carthy et al. (2003)

slope (2.24 0.39)

Cooray (1999)

slope (1.87 0.31)

Benson et al. (2004)

slope (2.79 0.51)

Scaling relations:Scaling relations:(iii) SZ flux decrement vs. X-ray e.w. temperature(iii) SZ flux decrement vs. X-ray e.w. temperature

self-similar expectation: self-similar expectation: S d S dAA22 E(z) E(z) T T5/25/2

Simulated clusters: slope (2.41 0.11)

Real clusters:

Benson et al. (2004)

slope (2.26 0.38)

How the cluster SZ properties How the cluster SZ properties depend on the physical processesdepend on the physical processes

included in the simulations?included in the simulations?

in collaboration within collaboration with

A. Bonaldi, PadovaA. Bonaldi, Padova

K. Dolag, GarchingK. Dolag, Garching

E. Rasia, PadovaE. Rasia, Padova

G. Tormen, PadovaG. Tormen, Padova

The hydro-simulationsThe hydro-simulations

The sample of 11 simulated clusters has The sample of 11 simulated clusters has been extracted from been extracted from HuttHutt ( (HHigh resoligh resolUUtion tion clusclusTTer seer seTT, Dolag et al. 2005), Dolag et al. 2005)

Mass resolution for gas particles: 2 x 10Mass resolution for gas particles: 2 x 1088 solar massessolar masses

Masses at z=0 are between 2 x 10Masses at z=0 are between 2 x 101414 and 2 x and 2 x 101015 15 solar massessolar masses

(Mass-weighted) temperatures are between (Mass-weighted) temperatures are between 1 and 10 keV1 and 10 keV

4 different sets of physical 4 different sets of physical processes included in the processes included in the

simulationssimulations

Gas:Gas: only adiabatic gas

Gas_nv:Gas_nv: low-viscosity scheme

Csf:Csf: cooling, star formation and SN feedback

Csfc:Csfc: like csf plus thermal conduction

SZ profilesSZ profiles

Solid: gas

Dashed: gas_nv

Dashed-dotted: csf

Dotted: csfc

Physical processes are changing the Physical processes are changing the

SZ profiles in the central regions, SZ profiles in the central regions,

mainly in small objectsmainly in small objects

Scaling relations:Scaling relations:yy00 vs. T vs. TMM

Expected slope from Expected slope from

self-similar model is 1.5:self-similar model is 1.5:

from the simulationsfrom the simulations

we obtain values between we obtain values between

1.3 for gas_nv 1.3 for gas_nv

and 1.8 for csfc.and 1.8 for csfc.

No effects for theNo effects for the

yy00-L-Lxx and and S-T relations,S-T relations,

where we recover the where we recover the

expected slopes 0.75 and 2.5 expected slopes 0.75 and 2.5

independently of the physicsindependently of the physics

SZ SimulatorSZ Simulator

Convolve IMAGE with instrumental DIRTY BEAM Convert y-parameter into measured flux [mJy] Add gaussian thermal noise at the appropriate level (exposition time depending) Smooth image to reduce noise Run CLEAN deconvolution algorithm

CLUSTER y map

Instrument DIRTY BEAM

Anna Bonaldi

OBSERVED CLUSTER

Observation report file

Simulated cluster

Observed cluster

AMI “survey mode” Kneissl et al. (2001)

FWHM=4.8 arcmin

The “observed” SZ profilesThe “observed” SZ profiles

First conclusionsFirst conclusions

Gas-DM velocity biasGas-DM velocity bias is negligible is negligible Internal bulk flowsInternal bulk flows introduce introduce 200 km/s 200 km/s

uncertainty (Holder 2003; Nagai et al. 2003)uncertainty (Holder 2003; Nagai et al. 2003) Using Using TTXX rather than T rather than Tee can introduce a serious can introduce a serious

overestimate of the peculiar velocityoverestimate of the peculiar velocity The simulated The simulated scaling relationsscaling relations agree with self- agree with self-

similar predictions and (roughly) with similar predictions and (roughly) with observationsobservations

But possible dependences on But possible dependences on physical processes physical processes and instrumental propertiesand instrumental properties

The contribution from The contribution from the cosmic webthe cosmic web

in collaboration within collaboration with

M. Roncarelli, BolognaM. Roncarelli, Bologna

S. Borgani, TriesteS. Borgani, Trieste

K. Dolag, GarchingK. Dolag, Garching

plus the KP collaborationplus the KP collaboration

MAPMAKINGMAPMAKING(1.9 deg)2 (3.8 deg)2

1. Choice of the right output2. Randomization3. Overlapping

Roncarelli et al. in preparation

Computational problem:to recover the past-light coneup to z=6 we need to use90 outputs, i.e. 1 Terabyte ofdata!

10 different maps available now

Thermal Sunyaev-Zel’dovich Thermal Sunyaev-Zel’dovich effect effect

yy - parameter - parameter

Redshift contributionto the y-parameter

Mean y - parameter:Total: 1.19 x 10-6

WHIM: 6.90 x 10-7

Kinetic Sunyaev-Zel’dovich Kinetic Sunyaev-Zel’dovich effecteffect

bb - parameter - parameter

Angular correlation function forAngular correlation function forthermal SZthermal SZ

Future stepsFuture steps

Complete statistical analysis of an extended Complete statistical analysis of an extended set of mapsset of maps

Clustering analysis of SZ and X-ray maps Clustering analysis of SZ and X-ray maps plus cross-correlationplus cross-correlation

Detectability of high-redshift clusters with Detectability of high-redshift clusters with ALMA (and Planck) via realistic ALMA (and Planck) via realistic simulations of the observations simulations of the observations

Redshift evolution of the scaling relationsRedshift evolution of the scaling relations