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Outer regions of GCs

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Title: Outer regions of GCs


1
Outer regions of GCs
People involved Borgani, Brighenti, Brunetti,
Colafrancesco, De Grandi, Ettori, Ghizzardi,
Mazzotta, Molendi, Moscardini, Rasia, Roncarelli,
Tozzi SRON (J. Kaastra) OBSERVATIONAL GOAL
To constrain surface brightness, temperature,
metallicity and bulk motion of the gas at Rvir.
2
  • SCIENTIFIC JUSTIFICATION
  • characterize the thermodynamic of the X-ray
    emitting
  • plasma at the virial radius
  • The above expanded in the following points
  • How reliable are the total mass measurements
    through the
  • hydrostatic equilibrium equation ?
  • Is any residual energy deposited in kinetic
    energy of the gas ?
  • How much of the gas mass fraction is measured
    within R200 ?
  • Implication calibrate the masses (gas and dark
    matter)
  • in local galaxy clusters to use them as
    cosmological
  • probes
  • 2) How is the metal enrichment process taking
    place in the cluster
  • outskirts where is (primordial?) cool gas
    accumulated ?

3
SCIENTIFIC JUSTIFICATION (cont.) 3) How can we
resolve smooth/lumpy accretion shocks at Rvir
? About that, note the following items 4) If we
are in condition to observe the outskirts of a
single galaxy clusters, we are definitely in
condition to map cluster merger even in their
early stage. An implication of this is that it
becomes justifiable the attempt to resolve the
excess in the hard X-ray due to no-thermal
emission in the cluster regions where the
interaction is taking place and the thermal
component is expected to be cool and soft.
4
  • WORK DONE SO FAR
  • ( PEOPLE THAT HAVE DONE THE WORK)
  • material at http//pico.bo.astro.it/ettori/outer/
  • (1) Physical properties of ICM at Rvir
  • Ettori, Molendi, Borgani
  • (2) Cosmological simulations
  • Borgani, Ameglio, Roncarelli, Tornatore
  • (3) Spectral simulations (3.a) background
  • Molendi, Ettori, Mazzotta
  • (4) No-thermal component
  • Brunetti, Vazza

5
(1) Physical properties of galaxy clusters at Rvir
  • Which gas density, temperature and surface
    brightness values do we expect at Rvir ?
  • Are simulated radial profiles consistent with
    extrapolation from observed data ?

6
(1) ICM at Rvir Simulated clusters
Tgas
ngas
Roncarelli et al
7
(1) ICM at Rvir Simulated clusters
Tgas
ngas
Unresolved CXB w. CXO (Hickox Markevitch 05)
Sb 0.5-2 keV
Roncarelli et al
8
(1) ICM at Rvir Simulated clusters
Simulations 4 massive objects Mvir 1.9-3.4e15,
Tvir 5.4-9.9 keV Rvir sphere that encloses a
mean density of 100 ?c Mvir 4/3 ? Rvir3 100
?c R2500, R500, R200 ? 0.2, 0.49, 0.74
Rvir Quant. 0.2Rvir 0.5Rvir
0.7Rvir 1.0Rvir ngas 1
0.127 (0.004) 0.051 (0.002) 0.018
(0.002) Tgas 1 0.735 (0.044)
0.613 (0.055) 0.491 (0.085)
9
(1) WHIM around GCs
Tgas
ngas
Roncarelli et al
10
(1) WHIM around GCs (r gt 1.2 Rvir)
11
(1) Surface brightness at Rvir observations vs
simulations
Rescaling everything to T3 kev and z0.035, we
find that --gt R500 0.5 Rvir simula mean
(disp) 6.75e-16 (1.20e-16) erg/s/cm2/arcmin2 2
objs in Mohr etal 4.94e-16 - 2.07e-15,
3.58e-16 - 2.65e-15 erg/s/cm2/arcmin2
Osservations / Simulations 0.5/4 Note that the
extrapolation from Mohrs data use (i) R500 from
both R-T relation and direct estimate from
beta-model, (ii) 2 beta values, the observed one
and 0.8, more reliable for the steepening of the
surface brightness in the outskirts. --gt
Rvir simula mean (disp) 3.30e-17 (1.06e-17)
erg/s/cm2/arcmin2 2 objs in Mohr etal
3.90e-17 - 2.89e-16, 2.80e-17 - 4.62e-16
erg/s/cm2/arcmin2 Osservations / Simulations
1-14 We consider in the spectral simulations an
object at T3keV and z0.035 with brightness
8e-17 erg/s/cm2/arcmin2
12
(2) Cosmological simulations
  • The simulations that are available for analysis
    are the following
  • 4 clusters with Mvir(1-2.3)x1015 Msun/h (ICS
    from K. Dolag LCDM cosmology with ?80.9)
  • Code GADGET-2 (Springel 2005)
  • Physics Z-dep. Cooling, SF, feedback, chemical
    enrichment from SNIa, SNII and AGB (Tornatore et
    al. 04, 06)
  • Maps of Compton-y, gas density, SBX (0.5-2
    keV), Tmw, Tew, Tsl, Si, O, Fe (S. Ameglio)

13
?gas
?X
Y
4 Rvir
Tew
Tsl
Tmw
O
Si
Fe
14
(2) Cosmological simulations
Available products - Maps of the described
quantities - Fits files (or idl procedure to
generate them) for all the maps, along three
projection directions Upon request -
Metallicity with other weights all
mass-weighted - Spectral maps (E. Rasia) - Maps
of velocity and velocity dispersion - Maps of the
Mach number (see Brunetti)
15
(3) Spectral simulations with Micro-calorimeter
and WFXRT
  • Files with the modeled background (local CXB
  • instrumental) in XSPEC and responses of the
    WFXRT
  • Micro-calorimeter were prepared.
  • We use a bash script (simback.sh) that calls
    XSPEC11 and
  • does
  • Faked spectra with random flactutations with
    assigned
  • amplitude in bkg
  • b. Faked spectra of given cluster model bkg
  • c. The joint-fit src bkg files to constrain T
    and EI.
  • Simulations with Micro-calorimeter already
    circulated
  • (molendi_micro.ps Molendis talk).

16
(3) Spectral simulations RESULTS with
Micro-calorimeter
(See Molendis talk)
  • Up to 0.6 Rvir, velocity measurements in the
    order of 100-200 km/s can be performed surface
    brightness can be measured if systematics error
    on fluxes can be kept lt few per cent. EW of O
    VIII can be derived. Abundances can be measured
    if T is known. Estimates of T from Fe-L shell
    forest only for cool systems.

17
(3) Spectral simulations RESULTS with
Micro-calorimeter
  • At Rvir we observe in the range (0.6296-.6336)
    keV
  • (4 eV bin around the peak in O VIII line at
    0.6537 keV
  • cluster rest-frame) the following number counts
  • kT n_cts_bkg n_cts_ICM sigma_det
  • texp1e6 sec, f_cxb0.8 fluctuations at 1,
  • 1 353 54
    2.9
  • 3 350 42
    2.2
  • 5 352 35
    1.9
  • texp1e6 sec, f_cxb0.3 fluctuation5
  • 1 181 30
  • 143 73
    2-4
  • 5 162 28 2.2

18
(3) Spectral simulations RESULTS with
Micro-calorimeter
To reach Rvir it is required to improve
significantly the instrumental properties, either
in spatial or spectral resolution. Reduction of
extragalactic bkg by a factor of 3 by resolving
70 of CXB with 5 PSF allows to resolve line at
Rvir. Otherwise, improvement by a factor of 5 in
spectral resolution, i.e. FWHM 0.4 eV. Expected
line broadening does not permit further
improvements. Improvements in effective area are
not critical.
19
(3) Spectral simulations RESULTS with
Micro-calorimeter
NOTE all these results are based on realistic
assumptions but must be taken with some caution.
To make line measurements the major obstacle is
the fore/back-ground emission. Our simulations
consider average properties of the galactic
foreground, about which (1) very little is known
on the spectrum (see McCammon et al. 2003), (2)
these estimates refer to 1 sr and we know from
RASS that strong spatial variations are expected.
20
(3) Spectral simulations RESULTS with WFXRT
Joint-fit src bkg spectra INPUT T 3 keV,
Sb8e-17, texp1e6, ARFpn_off_axis_exp.arf Resul
ts after 100 MC simulations (16-50-84 percentile
relative err) err0 T
-35 46 K -9 11
err1 T -28 72
K -13 16 err1, arfexp6 T
-26 47 K -14 10 err1,
texpbkg10x T -28 40 K -13
10 err5 T -43
gt100 K -26 37
21
Bkg dominant in GCs outskirts

Instr Bkg vs Src (XEUS / WFXRT) focal L2 /
Aeff (35m/3m)2 / (5e4/1500) 4 (x2 orbit
LEO/L2) (XEUS / XMM) 0.7
local gal
CXB
cluster
instr
22
(3) Spectral simulations RESULTS with WFXRT
At Rvir, for typical exposure time of 1e6 sec, we
can put constraints with relative error 1? of
30 on T and of 15 on EI by a joint-fit of the
source bkg spectra. To do this, we require to
take under control the fluctuations on the
background component at 1 level. With spatial
fluctuations of 5, the relative error on T and
EI measurements rise to gt45 and 30,
respectively. No much improvement is obtained by
increasing the effective area up to 6 keV.
23
(3) Spectral simulations RESULTS with WFXRT
The greatest concern is about the capacity to
control the modelling of the background
components affected from spatial variations up to
the requested level of 1. The joint-fit
extended to background spectra observed with
microcalorimeter can help in the modelling.
24
(3) Spectral simulations RESULTS with
WFXRTcalorimeter
Joint-fit src bkg spectra Unresolved CXB 0.3
wfxrt 0.8 calorim
Results after 50 MC sim err1 T
(-25, 39) K ( -7, 12) err5
T (-67, gt100) K (-67, 24)
25
(4) No-thermal component
See Brunettis talk
On the mergers, we are interested to have some
expectations on the hard X-ray emission
(brightness and spectral shape) in the different
stage of the mergers. Remember If we are in
condition to observe the outskirts of a single
galaxy clusters, we are definitely in condition
to map cluster merger even in their early
stage. An implication of this is that it becomes
justifiable the attempt to resolve the excess in
the hard X-ray due to no-thermal emission in the
cluster regions where the interaction is taking
place and the thermal component is expected to
be cool and soft.
26
Conclusions
  • We know what wed observe at Rvir (Tgas, Sb)
  • WFXRT At Rvir, for typical exposure time of
    1e6 sec, we can put constraints with relative
    error 1? of 30 on T and of 15 on EI by a
    joint-fit of the source bkg spectra. We require
    to take under control the fluctuations on the
    background component at 1 level.
  • micro-cal Up to 0.6 Rvir, velocity
    measurements in the order of 100-200 km/s can be
    performed surface brightness can be measured if
    systematics error on fluxes can be kept lt few per
    cent. EW of O VIII can be derived. Abundances can
    be measured if T is known. Estimates of T from
    Fe-L shell forest only for cool systems.
  • Constraints on the physical properties at Rvir
    cannot be reached.

27
Conclusions
  • NOTE all these results are based on realistic
    assumptions but must be taken with some caution.
  • The major obstacle for spectral measuraments is
    the subtraction of the fore/back-ground emission.
    Our simulations consider average properties of
    the galactic foreground CXB. In particular, the
    former is expected to vary spatially in a
    significant way.
  • We need to control the modelling of the
    background components affected from spatial
    variations up to the requested level of 1.
  • Which are the best targets ?
  • Low nH, high T, possibly with QSOs in the bkg,
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