text:
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arXiv:0902.2131v2 [astro-ph.CO] 6 Nov 2009
Astronomy & Astrophysics manuscript no. 11746ms
November 6, 2009
c ? ESO 2009
Multi-frequency imaging of the galaxy cluster Abell 2163 using the
Sunyaev-Zel'dovich Effect
M. Nord1,2,⋆, K. Basu1,2, F. Pacaud1, P. A. R. Ade3, A. N. Bender4, B. A. Benson5, F. Bertoldi1, H.-M. Cho6, G.
Chon1,2, J. Clarke5, M. Dobbs7, D. Ferrusca5, N. W. Halverson4, W. L. Holzapfel5, C. Horellou8, D. Johansson8, J.
Kennedy7, Z. Kermish5, R. Kneissl2, T. Lanting7,9, A. T. Lee5,10, M. Lueker5, J. Mehl5, K. M. Menten2, T. Plagge5, C.
L. Reichardt5, P. L. Richards5, R. Schaaf1, D. Schwan5, H. Spieler10, C. Tucker3, A. Weiss2, and O. Zahn5
1Argelander Institute for Astronomy, Bonn University, Bonn, Germany
2Max Planck Institute for Radioastronomy, 53121 Bonn, Germany
3School of Physics and Astronomy, Cardiff University, CF24 3YB Wales, UK
4Center for Astrophysics and Space Astronomy, University of Colorado, Boulder, CO, 80309, USA
5Department of Physics, University of California, Berkeley, CA, 94720, USA
6National Institute of Standards and Technology, Boulder, CO, 80305, USA
7Physics Department, McGill University, Montreal, Canada H2T 2Y8
8Onsala Space Observatory, Chalmers University of Technology, 43992 Onsala, Sweden
9D-Wave Systems Inc., Burnaby, Canada V5C 6G9
10Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
Received ... ; accepted ...
Context. Observations of the Sunyaev-Zel'dovich effect (SZE) from galaxy clusters are emerging as a powerful tool in cosmology.
Besides large cluster surveys, resolved SZE images of individual clusters can shed light on the physics of the intra-cluster medium
(ICM) and allow accurate measurements of the cluster gas and total masses.
Aims. We used the APEX-SZ and LABOCA bolometer cameras on the APEX telescope to map both the decrement of the SZE at
150 GHz and the increment at 345 GHz toward the rich and X-ray luminous galaxy cluster Abell 2163 at redshift 0.203. The SZE
images were used, in conjunction with archival XMM-Newton X-ray data, to model the radial density and temperature distribution of
the ICM, as well as to derive the gas mass fraction in the cluster under the assumption of hydrostatic equilibrium.
Methods. We describe the data analysis techniques developed to extract the faint and extended SZE signal. We used the isothermal β
model to fit the SZE decrement/increment radial profiles. We performed a simple, non-parametric de-projection of the radial density
and temperature profiles, in conjunction with X-ray data, under the simplifying assumption of spherical symmetry. We combined
the peak SZE signals derived in this paper with published SZE measurements of this cluster to derive the cluster line-of-sight bulk
velocity and the central Comptonization, using priors on the ICM temperature.
Results. We find that the best-fit isothermal model to the SZE data is consistent with the ICM properties implied by the X-ray data,
particularly inside the central 1 Mpc radius. Inside a radius of ∼1500 kpc from the cluster center, the mean gas temperature derived
from our SZE/X-ray joint analysis is 10.4 ± 1.4 keV. The error budget for the derived temperature profile is dominated by statistical
errors in the 150 GHz SZE image. From the isothermal analysis combined with previously published data, we find a line-of-sight
peculiar velocity consistent with zero; vr= −140 ± 460 km/s, and a central Comptonization y0= 3.42 ± 0.32 × 10−4for Abell 2163.
Conclusions. Although the assumptions of hydrostatic equilibrium and spherical symmetry may not be optimal for this complex
system, the results obtained under these assumptions are consistent with X-ray and weak-lensing measurements. This shows the
applicability of the simple joint SZE and X-ray de-projection technique described in this paper for clusters with a wide range of
dynamical states.
Key words. Galaxies: clusters: individual: Abell 2163 – Cosmic microwave background – Cosmology: observations
1. Introduction
The Sunyaev-Zel'dovich effect (SZE, Sunyaev & Zel'dovich
1970, Birkinshaw 1999) provides a powerful probe of the large-
scale structure in the Universe by imprinting the thermal energy
of clusters of galaxies on the cosmic microwave background
(CMB). The inverse Comptonscattering of CMB photonsby the
hot intra-cluster medium (ICM) has a characteristic frequency
dependence and a power spectrum that is very different from
that of the primary CMB anisotropies.
⋆e-mail: email@example.com
A numberof blind SZE imaging surveysare in progress(e.g.
Ruhl et al. 2004, Kosowsky 2006) with the aim of tracing the
large-scale structure of the Universe through the detection of
galaxy clusters, and the first blind SZE detections have recently
been reported (Staniszewski et al. 2009).
information on the X-ray surface brightness, the SZE thus pro-
vides constraints on gas temperatures and total mass distribu-
tions inside clusters. Such constraints are free of the potential
biases of X-ray spectroscopy. A further comparison with weak-
lensingmapsyieldsinsightintothedynamicalstate ofthecluster
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2 M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
Joint de-projection methods using X-ray and SZE maps have
been proposed (e.g. Lee & Suto 2004, Puchwein & Bartelmann
2006), but so far their implementation using real SZE data has
been limited to unresolved or barely resolved SZE maps (e.g.
De Filippis et al. 2005). Kitayama et al. (2004) presented the
first tempertauredeprojectionof a cluster using a combinedSZE
and X-ray analysis. However, this analysis was limited to using
a parametric model for the SZE signal. One main objective of
this paper is to show the potential of such a de-projection anal-
ysis using high signal-to-noise resolved SZE maps without the
limitations of parametric models.
Abell 2163 is a hot, X-ray luminous galaxy cluster at z =
0.203, with a mean X-ray temperature in the central region of
atively large angular extent, with a virial radius estimated from
weak-lensingmass modelingto be on the orderof 15 arcminutes
(Radovich et al. 2008), making the primary CMB anisotropies
a major source of systematic uncertainty in the SZE measure-
ments. Detailed X-ray observations suggest that Abell 2163 is
a merger system (Elbaz et al. 1995, Govoni et al. 2004), with
asymmetric X-ray temperature structures and strong radio ha-
los. The merger scenario is also supported by optical observa-
tions, most notably from the presence of two bright cD galax-
ies (BCGs; Maurogordato et al. 2008). The cluster has been ob-
served in the SZE at 30 GHz with OVRO/BIMA (Reese et al.
2002), and at 142, 217, and 268 GHz using SuZIE (Holzapfel et
al. 1997a,b).Using relativistic correctionsto the SZE, Hansen et
al. (2002)used these datato directlyconstrainthe meanICM gas
temperature in Abell 2163, albeit with very large uncertainties.
During the commissioning observation of the APEX-SZ
bolometer camera (Schwan et al. 2003, Dobbs et al. 2006) in
2007, we detected Abell 2163 with high significance (12σ) at
150 GHz with arcminute resolution. We observed the cluster in
the SZE increment at 345 GHz using the LABOCA bolometer
camera (Kreysa et al. 2003, Siringo et al. 2009) on APEX, pro-
viding images with an angular resolution of 19.5′′.
With amaplargerthan12′across,thepresentLABOCA data
on Abell 2163 provide the first large-area imaging of a galaxy
cluster at sub-mm wavelengths. High-resolution SZE increment
imaging is important in view of planned future observations of
clusters at sub-mm wavelengths, and for controlling potential
foregrounds. However, due to limitations in constraining the SZ
emission at large radii, the use of the sub-mm data in this paper
is limited to the application of the multi-frequency SZE mea-
surement to model the SZE spectrum and derive constraints on
the thermal and kinematic SZE components.
In sections 2 and 3 we describe the observations and data
reduction algorithms used to obtain maps at 150 and 345 GHz.
We also describe the analysis of complementary XMM-Newton
data. In section 4, a simple isothermal model of the cluster
gas density distribution is presented. A joint SZE/X-ray de-
projectionof the cluster temperatureand density structureis per-
formed in section 5. Finally, we incorporate all available SZE
observationsof Abell2163in section 6 to derivethe best-fit line-
of-sight peculiar velocity and central Comptonization from the
SZE spectrum. We list our conclusions in section 7.
−1.1keV (Markevitch & Vikhlinin 2001). It has a rel-
2. Observations
2.1. APEX-SZ observations at 150 GHz
ObservationsofAbell 2163at 150GHz werecarriedoutin April
2007 with the APEX-SZ bolometer camera, with a measured
beam full-width half-maximum (FWHM) of 58′′(determined
from observations of Mars) and an effective bandwidth of 23
GHz (Halverson et al. 2008, hereafter H09). At the time of ob-
servation, 280 of the 330 bolometers were read out, and of these
about 160 were used for the map making after applying a noise
cutoff (section 3).
To obtain a uniform coverage over the extended emission of
the cluster, horizontal raster scans were made with a 15′× 15′
scan pattern, tracking the central cluster position. The median
scan speed was 230′′s−1, and the total integration time was 7.6
hours. The observing conditions were good to moderate for the
site, with 150 GHz zenith opacities in the range 0.04-0.09.
Totest adifferentscanstrategy,0.8hoursofadditionalobser-
vations were carried out in August 2007, scanning in circles of
radius 6 arcminutes. At the beginningof each 2-minute subscan,
the circle center was placed on the cluster center, and during the
subscan the source was allowed to drift throughthe scan pattern.
2.2. LABOCA observations at 345 GHz
Afterproducinga highsignal-to-noisedetectionwithAPEX-SZ,
five hours of follow-up observations at 345 GHz with LABOCA
were completed in September 2007. Seven further hours of ob-
servations at this frequency were carried out in May 2008.
At the time of observation, LABOCA had 268 optically ac-
tive bolometer channels, of which around 240 were used for
mapping of Abell 2163. From observations of Neptune the co-
added beam size was determined to be 19.5′′(FWHM). The ob-
serving conditions were stable in both observing periods, with
a typical atmospheric zenith opacity of 0.2-0.3 at the observing
frequency.Abell 2163 was observed in an elevation range of 40-
70 degrees.
For the LABOCA observations, a spiral pattern was used
with inner and outer radii of 120 and 180 arcseconds, respec-
tively. Each scan was made up of four such spirals, separated by
140 arcseconds in azimuth and elevation, to make the coverage
close to constant over the central part of the cluster.
2.3. X-ray observations
X-ray emission originating from clusters provides additional in-
formation on their ICM, and in the interpretation of our results
we make use of archival XMM observations of Abell 2163. The
cluster was observed in August 2000 as part of the guaranteed
time from the first year of operation. Due to the large size of the
target, as compared to the XMM field of view, a mosaic of five
pointingswas requiredto fullycoverthe cluster: one 'on-source'
pointing1and four offset pointings2to probe the outskirts of the
cluster and the surrounding cosmic background. The nominal
exposure time of each observation was about 30ks. Since the
full exposure could not be achieved for the 'on-source' point-
ing, the observation was completed with a second pointing3in
September 2001, which is included in our analysis.
3. Data reduction, calibration and mapping
3.1. General sky-noise considerations
The SZE signal from Abell 2163 is extended over more than
20 arcminutes, which is comparable to the field-of-view of
1Observation Id: 0112230601
2ObsId: 0112230701, 0112230801, 0112230901, 0112231001
3ObsId: 0112231501
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M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect3
APEX-SZ (23′across) as well as that of LABOCA (11′across).
This makes the subtraction of atmospheric signals very difficult;
subtracting common-mode signals across the array and apply-
ing polynomial baselines (corresponding to large-scale Fourier
modes) in this case has the side effect of also removing astro-
nomical signals on scales comparable to the field-of-view of the
The properties of the two instruments used in this anal-
ysis differ substantially, calling for highly specialized reduc-
tion schemes in each case. In general, the APEX-SZ observa-
tions were carried out in poorer observing conditions than the
LABOCA observations, with relatively high levels of precip-
itable water vapor. For this reason, the APEX-SZ data suffers
from excess low-frequency noise correlated on scales smaller
ter time streams to be applied after removing the correlated at-
mospheric signal. While this step enhances the signal-to-noise
ratio of the detection, it also removes additional astrophysical
signal. To account for this, we make use of a point source trans-
fer function as in H09. It is used as follows: (i) for the isother-
mal analysis, we model the cluster by convolving the param-
eterized cluster model with the transfer function and compare
the result with our reduced map; and (ii) for the non-parametric
non-isothermal analysis, we deconvolve the reduced map with
the transfer function.
In spite of the higher frequency band, there is no excessive
low-frequencyatmosphericnoise componentin the time streams
of the LABOCA data. However, because of the lower sensitiv-
ity of this instrument with respect to the SZE signal, a smaller
scan pattern was used, compared to the APEX-SZ observations,
to maximize the signal-to-noise ratio in the limited time avail-
able. The small scan pattern fundamentally limits the scale on
which the SZE signal can be recovered. In addition, the details
of the LABOCA data reduction limits the use of a transfer func-
tion since the latter cannot be constructed to be linear; in other
words, the reduction pipeline acts differently on a point source
and an extended source. To recover as much of the SZE incre-
ment signal as possible, we use a slightly modified form of the
iterative map-making algorithm outlined by Enoch et al. (2006).
software BoA4has been used.
3.2. Calibration of the millimeter data
Primary flux calibration for APEX-SZ and LABOCA relies on
observations of planets. The APEX-SZ data is calibrated with
on the sky are determined for each bolometer. After adjusting
the bolometer relative calibrations and angular offsets derived
from the Mars observations, a co-added rms weighted map is
made using all optically active bolometers. This map is used to
determine the overall calibration factor, taking into account the
significant side lobes of the beam.
The calibration procedure is similar for LABOCA, but here
the primary calibrator is Neptune, which remains unresolved in
the 19.5′′beam. Because Neptune was not always observable,
several secondary calibrators were used for LABOCA (Siringo
et al. 2009). These sources used have been monitored by the
LABOCA team since early 2007, and their 345 GHz flux densi-
ties, relative to Neptune, are known to within about 6%.
Theabsolute flux of Mars at the APEX-SZ frequencyat each
observingperiod is determinedusing a modification of the Rudy
model (Rudy et al. 1987; Muhleman & Berge 1991),maintained
by Bryan Butler5and corrected to be in agreement with recent
WMAP results as described in detail in H09. The absolute flux
of Neptune at 345 GHz is derived from cross-calibrations of
Neptune against Mars (Griffin & Orton 1993).
To monitor the stability of opacity correctionsat different el-
putation of opacities relies on skydip measurements combined
with tau-meter readings (Weiss et al. 2008, Siringo et al. 2009).
3.3. APEX-SZ data reduction
Time stream data from APEX-SZ is processed through a data
reduction pipeline and binned to form maps. This process is de-
scribed here. The pipeline is slightly different for raster scans
and circular drift scans, but identical for each scan within these
two subsets.
After eliminating detectors with low optical response, corre-
lated (atmospheric and electronic) noise is removed by subtract-
ing the median signal from across the good channels of the array
at each time sample. Individual time streams are then despiked
by flagging and removing data that deviates from the baseline
by more than 5σ, which typically corresponds to less than 0.1%
of the data.Electronicglitches are recognizablebecausetheyoc-
cur with durationsshorter than the detectorresponse time. These
features, seen only in a negligible amount of data, are removed
as well.
To baseline the data of a raster scan, the scan is divided
into subscans of constant elevation, resulting in subscans ex-
tending over 30′in azimuth. Turnarounds in the scan pattern,
where the scan speed is significantly lower, are flagged and re-
moved. A fifth order polynomial is fitted to and subtracted from
each constant-elevation subscan, effectively high-pass filtering
the time streams.
Circular drift scans are baselined by defining subscans con-
sisting of 2.5 full circles and applying a fifth order polynomial,
after flagging the first full circle of the scan (which usually con-
tains intervals of high scan acceleration). This polynomial base-
line corresponds to a spatial filter similar to that applied to the
raster scans. Simultaneously, an airmass correction is applied as
described in H09.
For each scan, a map with 10′′× 10′′sized pixels is con-
structed, weighting the data by the inverse rms of each reduced
time stream. All maps are then co-added. In parallel with the
reduction of the data, a beam-shaped source, without noise and
translated into time stream data, is passed through an identical
pipelineto obtainthe pointsourcetransferfunction,as described
by H09. All flags and weights on the data are carried over to the
artificial data.
Theresultingtransferfunctionis usedtodeconvolvethehigh
significance co-added map of Abell 2163 to the intrinsic reso-
lution of the instrument. The deconvolution is done iteratively,
and is similar to the CLEAN algorithm for interferometry data
(H¨ ogbom1974,Schwarz1978)inthat thesourceis modeledas a
sum of many point sources; here, however,the process is carried
out in map space rather than Fourier space. The raw (pipeline
filtered) map, M0, is first convolved with the beam to reduce the
sample variance on small spatial scales. Each pixel in the map
is then divided by the local rms to create a signal-to-noise map,
N0, from which the brightest pixel is selected. The correspond-
5http://www.aoc.nrao.edu/ bbutler/work/mars/model
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4M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
ing point source flux corresponding to this peak pixel value is
computed, taking into account both the beam smoothing of M0
and the complete description of the inherent resolution and the
effects of the reduction described by the point source transfer
function. The resulting point source is re-convolved with the
transfer function to represent how the point source is reflected
in the raw map. This component is subtracted from M0to yield
M1, from which a new smoothed signal-to-noise map N1is con-
structed. The point source is also convolved with the "clean"
beam and added to a map C of "clean component". Next, the
brightest pixel in N1is located, and the process is repeated un-
til Miis consistent with noise. The criterion for the latter is that
as many negative as positive pixels are selected in any consec-
utive 20 iterations. At this point, Miis added to the cumulative
map C to account for emission which has not been successfully
removed as point sources. Details on the limitations of this de-
convolutiontechniquewill begiveninafuturepublication(Nord
et al., in preparation).Thede-convolvedAPEX-SZ mapof Abell
2163 is shown in Figure 1.
To compute the noise on the beam scale, we smooth the fi-
nal map with the APEX-SZ beam (FWHM 58′′and computing
the rms in square regions with side five times the beam. In this
way, we find a noise rms value of 32 µKCMBon the beam scale,
correspondingto 0.013 MJy sr−1, in the central region of the de-
convolved map.
Fig.1. Map of Abell 2163 at 150 GHz, overlaid with
XMM-Newton X-ray contours (see Fig. 3) in units of
10−13ergs−1cm−2arcmin−2. Because the correlated-noise re-
moval has attenuated the source signal, the map has been de-
convolved using the point source transfer function (see text).
3.4. LABOCA data reduction
Because the LABOCA time streams are more stable at low fre-
quencies than those from APEX-SZ, the data do not have to
be further filtered after standard correlated-noiseremoval. Aside
from this difference, the time stream reduction sequence used in
each iteration is quite similar to that used for the APEX-SZ data,
and basically follows the method outlined by Weiss et al. (2008)
and detailed by Siringo et al. (2009). Maps are constructed with
6′′× 6′′pixels, and co-added in the same way as for the APEX-
SZ data.
To account for sky signal attenuation in the time stream re-
duction, we follow the iterative approach of Enoch et al. (2006),
with one important modification. Using a suitably chosen time
stream reduction algorithm, a map is produced. Each pixel with
a significance of less than 3 sigma is set to zero, and the rest of
the map is chosen as the template to be subtracted directly from
the time streams before running the same time stream reduction
yet again, and so on. While Enoch et al. take a conservative ap-
proach and derive the next template from the residual signal, we
add the template back into the data prior to mapping and derive
this template from the total map. This ensures that any signifi-
cant feature in the current best guess of the source flux distribu-
tion is carried over to the next iteration step.
The iterative mapping algorithm requires 8 iterations before
convergenceis reached.Ineach iteration,an identicaltime series
reduction is performed.
Because the iterative mapping technique is non-linear, it is
not straightforwardto characterizeit bya filter function.In place
of a transfer function,the instrument beam is used when fitting a
model to the 345 GHz data. Significant loss of signal is expected
using the iterativeapproach.To quantifythe level of bias, we use
the best-fit β model from the APEX-SZ measurement (section
4) and pass is through the complete LABOCA data reduction
pipeline. Although more than 30% of the signal is lost beyond
r500(the radius at which the enclosed average matter overden-
sity is 500 times the mean cosmic density), we find that the sig-
nal loss within r2500(defined analogously, approximately 3′) is
negligible compared to statistical errors. The central rms in the
LABOCA map, computed on a scale of five times the LABOCA
FWHM (19.5′′), is 1.9 mJy/beam, corresponding to 0.24 MJy
We find one significant point source in the final map (Figure
source lensed by the cluster. After highpass-filtering the map
to remove structures larger than two beams (such as the cluster
emission), we find a peak flux density of 11.8 ± 1.9 mJy/beam
for this source.
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M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect5
Fig.2. Top: Final 345 GHz LABOCA map of Abell 2163,
smoothed with the 19.5′′beam. The cross marks the position
of a bright flat-spectrum radio source (Cooray et al. 1998). The
diamonds mark the positions of two BCGs (Maurogordato et al.
2008). The circle marks the position of the bright point source
found in the present data. Bottom: LABOCA map smoothed to
the APEX-SZ resolution of 1 arcminute. The bright point source
described in the text has been removed.The APEX-SZ 150 GHz
map is shown as contours.
3.5. XMM-Newton data reduction
Here we describe the processing steps applied to the X-ray data.
We generate calibrated event-lists from the raw data of the
6 archival pointings using the standard procedures of the XMM
Science Analysis System6(SAS) and screen these lists for pe-
riods of high radiation due to soft solar proton flares. To this
end, we apply the method of Pratt & Arnaud (2002), which con-
sists of fitting histograms of the high energy7light curves with
a Poisson law and rejecting time intervals exceeding the mean
radiation level by more than 3σ. On average, this shortens the
available exposure time by 15%. Although the high energy sig-
nal is verysensitive to particle flares, one needsto adopta coarse
time sampling (104s here) to ensure that the average number of
counts per bin is significant. This implies that the wings of light
6http://xmm.esac.esa.int/sas/, all the data processing for this paper
relies on v7.1.2
7more precisely [10-12] keV for the MOS detectors and [12-14] keV
for the PN
curve jumps in increased radiation periods cannot easily be de-
tected. To improve on our first filtering, we thus repeat the same
analysis on a broad low energy band, namely [0.3-10] keV with
narrowtimebins of13s,resultingin theexclusionofanextra3%
of the data. Out-of-time event lists are also generated using the
simulation mode of the SAS tasks emchain/epchain and filtered
using the same time intervals.
From the filtered event lists, images and exposure maps are
generated in the [0.5-2] keV band and gathered into two large
mosaics. The signal to noise of the cluster in this band is about
80% of the best achievable value using the XMM bands. It
is however free from the strongly varying instrumental lines
around 6-7 keV and calibration uncertainties at lower energies.
Combined with the weak dependence of the cooling function on
temperature at low energies (soft X-rays), this makes it a very
suitable band for our purpose. Since the XMM response is al-
most flat in this narrow band,the exposuremaps are evaluatedat
a single average energy of 1.25 keV.
The main issue in the X-ray analysis of extended source is
an accurate background modeling. To this end, we make use of
the Filter Wheel Closed (FWC) dataset provided by the XMM
background working group8. Our model consists of a sum of a
re-scaled FWC image (which represents the instrumental noise),
an homogeneous cosmic background of constant surface bright-
ness (since the area of the mosaic remains small) and a properly
scaled image of the out-of-fieldevents.The scaling of the instru-
mental background is allowed to vary with each pointing and
instrument while the cosmic background level is just a function
of the detector (to account for the different responses). Using the
Cash statistics (Cash 1979), the model parameters are fitted si-
multaneously to the 6 observations including the data from the
out of field corners and excluding the positions closer than 17′
from the cluster center.
In orderto detect and mask the surroundingAGNs, we adap-
tively smooth the background subtracted raw mosaic, using the
criterion of having more than 10 counts per cell. The resulting
map is then exposurecorrected and smoothed again by a σ = 2′′
Gaussian9. A source catalog is extracted from this image using
SExtractor (Bertin & Arnouts 1996) and the associated source-
segmentation map is combined with an exposure time threshold
in order to derive a global mask.
The tasks of backgroundestimation and source detection are
instrumental and particle backgroundvariations can occur in be-
tween pointings. To tackle this issue, we iteratively re-perform
the backgroundmodelingand AGN extractionusing the updated
AGN mask for the backgroundestimate. Both products stabilize
after three iterations.
Thefinal backgroundsubtracted,adaptivelysmoothedimage
of the cluster is shown in Fig. 3.
4. Isothermal modeling of the intra-cluster gas
In order to assess our SZE measurements quantitatively and
compare them with the X-ray data, we fit the SZE measure-
ments using the well-known isothermal β model (Cavaliere &
Fusco-Femiano 1978). This enables us to compare the X-ray
8http://xmm2.esac.esa.int/external/xmm sw cal/background/
9This hybrid smoothing allows to wash out the Poisson fluctuations
in regions devoid of source signal without degrading the resolution over
moderately bright sources (which are both the advantage and drawback
of adaptive filtering alone)
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6M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
Fig.3. Smoothed, background subtracted, X-ray map of
Abell 2163 in the [0.5-2] keV band (see text for details).
Logarithmically spaced contours highlight the broad dynami-
cal range of the cluster emission. The unit of the color scale is
surface brightness profiles with the SZE temperature decre-
ment/incrementmaps and check the agreement of our SZE mea-
surements with the prediction from the X-ray mean values.
4.1. Isothermal gas in hydrostatic equilibrium
The isothermal β model is widely used to model the gas profile
in clusters under the assumption of hydrostatic equilibrium. The
radial distribution of gas density is given by
ne(r) = ne(0)
1 +r2
where neis the density of electrons, r is the radius from the cen-
ter, rcis the core radius of the gas, and β is the power law index.
With this model, the temperature decrement (or increment)
due to the SZE takes the form
∆T(θ) = f(x,Te) TCMBy = ∆T(θ = 0)
1 +θ2
where θ is the angular radius on the sky, ∆T is the thermody-
namic SZE temperature decrement (or increment) and y is the
Comptonization parameter, given by the line-of-sight integral
y =
? ?kBTe
where σTis the cross section for Thomson scattering. The fre-
quency dependence f(x,Te) of the SZE signal is given by
f(x,Te) =
xex+ 1
ex− 1− 4
(1 + δx,Te),
with relativistic corrections contained in δx,Teas described by
Sazonov & Sunyaev (1998). x is the dimensionless frequency
x =
The analogous expression for the X-ray surface brightness
where S0is the central surface brightness and the different ex-
ponent comes from the n2
∆SX(θ) = S0
1 +θ2
edependence of X-ray emissivity.
4.2. Elliptical β model fit to the SZE data
Because of the significant ellipticity in the X-ray surface bright-
ness profile, we generalize equation2 to an elliptical formgiven,
e.g., in H09 as
∆TSZE= ∆T0(1 + A + B)(1−3β)/2,
A =(cos(Φ)(X − X0) + sin(Φ)(Y − Y0))2
B =(−sin(Φ)(X − X0) + cos(Φ)(Y − Y0))2
Here (X − X0) and (Y − Y0) are angular offsets on the sky in the
right ascension (RA) and declination (DEC) directions, respec-
tively, with respect to centroid position (X0, Y0). The axial ratio,
η, is the ratio between the minor and major axis core radii and Φ
is the angle between the major axis and the RA (X) direction.
An elliptical β profile is fitted to the 150 GHz data by con-
volving each model function with the point source transfer func-
tion and minimizinga χ2statistic weighted by the inverse square
of the local map rms. Note that the raw, not the de-convolved,
map is used for this fit in conjunction with the transfer function.
All map pixels within a 10′radius of the X-ray center (section
4.3) are considered for the fit. The results of the fit are given in
Table 1.
For comparison, we also fit a spherical β profile and find
roughly consistent results. At 345 GHz, the detection of Abell
2163 is less significant, we thus fix the centroid and the value of
β to those fitted from the 150 GHz measurement and fit for the
remaining parameters.
Errorsinthefitted profilesareestimatedusingaMonteCarlo
approach. The map data is jack-knifed by inverting the sign of
half the individual scan maps (randomly chosen), and the maps
are co-added to generate a pure noise map. After convolving the
best-fit model with the transfer function and adding the result
to the noise map, the χ2statistic is again minimized to find the
best set of parameters for the new map. The entire procedure
is repeated 1000 times, upon which the errors in the respective
parameters are taken as the scatter in the distributions of their
fitted values.We verifythatthe meanofthedistributionsoffitted
parameters are consistent with the best-fit model.
4.3. Elliptical β-model fit to the X-ray data
To allow fora basic comparisonofthe SZE and X-raydata in the
context of the isothermal β model, we perform an isothermal fit
to theX-raydata, similarto thatusedfortheSZE data.As forthe
SZE analysis, we generalize the spherical β model of equation 4
to the elliptical case, as:
∆SX= ∆S0(1 + A + B)1/2−3β,
Page 7
M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect7
This model is fitted to the raw X-ray images using the Cash
statistic (Cash 1979).The Poisson nature of the data does not al-
low here for a direct backgroundsubtraction; instead we add the
simple two-component background described in section 3.5 to
thefittedcomponents.Theresultsofthefit arepresentedinTable
4.4. Systematic uncertainties
4.4.1. Galactic dust
The effect of galactic dust emission on the SZE measurement
of Abell 2163 has been estimated by Lamarre et al. (1998) for
the PRONAOS balloonexperimentandbyLaRoqueet al. (2002)
for the SuZIE experiment (Holzapfel et al. (1997a,b)).However,
because these two estimates apply to scan strategies and spatial
filtering functions very different from ours, it is not appropriate
to extrapolate from either of them.
To estimate the dust correction at 345 and 150 GHz, we use
the IRAS far-infrared 60µm and 100µm dust maps (Schlegel et
al. 1998) on the Abell 2163 field . Smoothing the 60µm map to
the 4.3′resolution of the 100µm map and re-sampling the maps
so that each pixel has a side of one arcminute, we extrapolate
to the frequencies of the SZE measurements using a grey-body
spectrum of dust emissivity
exp(hν/kBTd) − 1,
where α is the dust spectral index. Using α = 2.0 (Finkbeiner
et al. 1999) we fit to Tdfor every 1′× 1′pixel pair in the two
dust maps. After smoothing the resulting temperature map with
a 4.3′Gaussian kernel to removenoise artifacts, we use equation
(7) to extrapolate the intensity at 345 and 150 GHz, normalizing
at 100µm.
The simplest way of removing the dust component from the
data is to subtract it before any filtering is applied by the re-
duction. We thus create time streams corresponding to the ex-
trapolated dust maps on the coordinates covered by APEX-SZ
and LABOCA and subtract these from the raw time streams be-
fore proceeding with reductions identical to those described in
section 3. In this way, we find corrections of -0.6% to the SZE
decrement at 150 GHz and +1.8% to the SZE increment at 345
GHz. Effects on the other fitted parameters are negligible. We
assume that contamination on angular scales smaller than four
arcminutes (i.e. not resolved by IRAS) are also negligible.
4.4.2. Point source contamination
After subtracting a preliminary (possibly point source contami-
nated) β model from each map, we smooth the maps to the re-
spective beam scales and look for point source detections above
3σ. One source (cf. Figure 2) is found in the LABOCA map at
345 GHz. No sources are found in the APEX-SZ 150 GHz map.
Point sources which are detected with sufficient S/N in the maps
could be removed by subtracting fitted Gaussians. Here we take
a somewhat more conservative approach and simply disregard a
region around the 345 GHz point source in a subsequent fit with
a new β model.
Extragalactic infrared point sources are not expected to cor-
relate spatially with clusters of galaxies, and a distribution of
sources can be well approximated by excess noise in any dif-
ferential measurement (White & Majumdar 2004), thus having
little systematic effect on bolometric SZE measurements.
Although lensing by a massive cluster such as Abell 2163
can significantly increase the number of detected sources in the
cluster central region, this effect conserves the total intensity of
the background and only becomes important when faint sources
are raised above the detection limit and removed, and the un-
resolved backgroundintensity is thereby systematically lowered
(e.g. Loeb & Refregier 1997). It is not clear whether the bright
point source found in the 345 GHz map is a lensed background
source; however, we have verified that the effect in fitted pa-
rameters of excluding the region around this source for the fit
is merely 4%, i.e. smaller than both the derived statistical errors
and the absolute calibration uncertainty.
Radio sources are expected to correlate strongly with clus-
ters of galaxies (e.g. Reddy & Yun 2004). We have searched the
NVSS catalog (Condon et al. 1998) for sources brighter than
5 mJy at 1.4 GHz. The flux of each source is extrapolated to
150 GHz using the spectral index maps of Feretti et al. (2004).
With this simple approach, even the brightest source will have a
peak flux considerablylower than the rms in the APEX-SZ map.
Cooray et al. (1998) report an inverted-spectrum non-thermal
sourceof 3 mJy at 30 GHz, indicatedin Figure 2. No counterpart
can be seen in eitherSZE map. High-passfilteringthe APEX-SZ
map, aftersubtractingthe best-fit model of the cluster,to remove
at the position of this source. The fact that the source is not seen
in this filtered map allows us to put a lower limit on the spectral
index as α150
signal from the APEX-SZ map before the β model fit results in
a systematic shift in the central SZE decrement of less than 1%.
Based on these considerations, we consider systematic effects
from radio sources negligible in comparison to primary CMB
anisotropies and absolute calibration.
30? 0.5 (Sν∝ ν−α). Subtracting the corresponding
4.4.3. Primary CMB contamination
For a very extended cluster like Abell 2163, with an estimated
r500 greater than 7′(Radovich et al. 2008), the temperature
anisotropies in the CMB are a potential source of confusion in
the SZE measurements. This uncertainty particularly affects the
kinematic SZE signal because the latter has a frequency depen-
dence identical to that of the CMB thermal spectrum. Note that
this is not an issue for CMB power on scales ? 15′due to the in-
direct high-pass filtering of our maps (through polynomial base-
lines in the bolometer time series).
To quantify the level of contamination on scales compa-
rable to the SZE emission, the HEALpix software (Gorski et
al. 2005) is used to generate 100 realizations of the CMB sky
in a one square degree field with a resolution of 1.7′. The in-
put power spectrum for this generation is computed using the
CMBfast code (Zaldarriaga & Seljak 2000) with the WMAP 5-
year cosmology (Komatsu et al. 2009). Relying on the results
of LaRoque et al. (2002), diffuse secondary CMB anisotropies
other than the SZE are considered negligible.
Each primary-CMB map is re-sampled as time streams cor-
responding to a typical scan of the SZE observations at the two
frequencies and run through the reduction pipelines to account
for filtering. The β model fit is repeated after subtracting each of
the thus filtered primary-CMB realizations. The scatter in the re-
sults of each parameter is taken as the 68% systematic marginal
error from primary CMB contamination.We find a fractional er-
ror of 3.4% at 150 GHz and 2.9% at 345 GHz.
The primary-CMB component has been simulated on the
relevant scales compared to the cluster emission, with scales
smaller than 1.7′not taken into account.This is justified because
Page 8
8M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
the power of the primary anisotropies drops rapidly on scales
smaller than a few arcminutes.
4.4.4. Pipeline filter function
To test how well the point source transferfunctionrepresents the
filteringoftheSZE signalinmapspaceat150GHz, wecarryout
a series of reductions of known signals. To this end, we remove
minute segments and randomly inverting half of these. Before
passing the noise data through the pipeline, a beam-convolved
β model is added to the time streams. The point source transfer
function is used to reconstruct the β model after reduction, and
the procedure is repeated for a large number of β models in the
range 50′′≤ θc ≤ 150′′, 0.5 ≤ β ≤ 1.4. We find no evidence
that the level of noise affects the result other than to increase the
scatter in fitted parameters; we thus use bright model sources
(∼ 10mKCMBat 150 GHz) to estimate the effect of the pipeline.
Although the fitted central amplitude can be systematically
reduced by as much as 12% for combinations of small β and
large θc(characterizing very broad profiles, where some modes
in themapareirrecoverablebythetransferfunction),we findthe
systematic shift to be no more than 2% for either of the models
fitted to the actual 150GHz data.Due to the degeneracybetween
β and θc, there is considerable scatter in these parameters when
fitted to the simulated data. Keeping one parameter fixed and fit-
ting the other, we find that the systematic errors in both param-
eters due to inaccuracies in modeling the pipeline filter function
are negligible.
4.5. Results of the isothermal modeling
Figure 4 shows the radial profile of the best-fit spherical β pro-
file to the 150 GHz data and the same profile convolved with
the transfer function, as well as the profiles of the raw and
de-convolved maps. The best-fit β model parameters, corrected
for systematic effects as described below, are given in Table 1.
dial profile of the de-convolved map is fully consistent with the
beam-smoothed best-fit model within the 10′truncation radius
used for the fit.
Comparing the results of the X-ray and SZE fits, a non-
negligible offset (21 ± 8′′), possibly caused by an asymmetric
temperature distribution near the center, appears between the
two centroidpositions. The originof this offset will be discussed
as part of further analysis in a future publication (Kneissl et al.,
in preparation).The other fitted parameters show an overall con-
sistency in the globalshape ofthe emission. We notethat in spite
of the significant ellipticity in the X-ray surface brightness, the
elliptical model of the SZE signal is only barely inconsistent
with the spherical one (the axial ratio deviates from 1 by only
1.7σ). The most likely explanations for this are the poorer reso-
lution of the SZE data which results in a greater uncertainty on
the ellipticity, and the inherent fact that the SZE signal, due to
the density weighting, is naturally smoother and more diffuse.
5. Non-isothermal modeling of the intra-cluster gas
Severalauthorshavediscussedthejoint modelingofSZE andX-
ray data for de-projectingICM parameters (see, e.g., Yoshikawa
Ameglio et al. 2007). However, most of these analyses have
beenlimitedto analyticcluster modelsornumericalsimulations.
Fig.4. Radial SZE profile of Abell 2163 at 150 GHz. Error bars
indicate the profile computed from the reduction-attenuatedraw
map (before deconvolution; this is the map used for the para-
metricfit) whilethe shadedregionrepresentsthe profilefromthe
mapde-convolvedtothe beamresolution(notethatthis mapwas
not used to derive the best fit β model. The profile of the best-fit
isothermal β model is indicated by solid lines; the thick line rep-
resents that model convolved with the beam, while the thin line
represents the same model convolved with the transfer function.
The dashed line indicates the profile of the de-convolved map,
directly re-convolved with the transfer function. The vertical ar-
rows indicates the radial cut of 10′used for the model fit, as well
as r200and r500.
Our work here represents the first attempt at de-projecting clus-
ter density and temperature profiles using actual SZE imaging
data, in combination with the X-ray data, without resorting to
any parametric models for the gas or dark matter distribution.
Given the large angular size of Abell 2163, the arcminute
resolution of APEX-SZ is sufficient to carry out a joint radial
density and temperature modeling of the ICM in combination
with publicly available X-ray data. Although the LABOCA map
has more than a factor of two better resolution, due to its high
noise level and small field of view we restrict the analysis in this
section to the APEX-SZ data.
5.1. Method
5.1.1. Deprojection method
For the deprojectionanalysis we use a direct inversiontechnique
based on the Abel integral. The technique was first proposed by
Silk & White (1978; see also Yoshikawa & Suto 1999). Apart
from the assumption of spherical symmetry, there are no ad-
ditional theoretical constraints (e.g. hydrostatic equilibrium or
polytropic gas index), making this is a natural method for ex-
tracting ICM parameters, assuming that spherical symmetry in-
deedprovidesa goodestimateofthe structure.Thedetailsofthis
method and its limitations will be discussed in a future publica-
tion (Basu et al., in preparation); here we present the outline of
the method and the results for Abell 2163. X-ray spectroscopic
measurements have shown that Abell 2163 has a complicated
temperature structure at the center and is most likely a merg-
ing system (Elbaz et al. 1995, Govoni et al. 2004). Nevertheless,
here shows how resolved SZE images of clusters can immedi-
Page 9
M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect9
Table 1. β model fit results at 150 and 345 GHz.
X0(Central R.A. [J2000])
Y0(Central DEC. [J2000])
Peak signala
θc(core radius)
β (power-law index)
Φ (inclination angle)
η (axial ratio)
150 GHz (elliptical)
150 GHz (spherical)
345 GHz (spherical)
X-ray (elliptical)
1.075 × 10−12±7 × 10−15
aBrightness in units of MJy sr−1(SZE), and in units of ergs−1cm−2arcmin−2(X-ray)
bFixed parameters indicated by parentheses
ately be used in combination with X-ray data to gain a better
understanding of the gas and mass distribution.
The deprojection analysis is based entirely on the radial pro-
files ofX-raysurfacebrightnessandSZE temperaturedecrement
(or increment). From equation (2) the SZE temperature decre-
ment can be written as the integral over the line of sight;
where the cluster is assumed to be spherically symmetric, ASZ=
σT(kTCMB/mec2),r isthephysicalradiusfromtheclustercenter,
R = DAθ where θ is the projected angular distance on the sky
and DA is the angular diameter distance (to calculate DA, we
assume the cosmology of Komatsu et al. 2009 for the remainder
of the paper). Te(r) and ne(r) are the electron gas temperature
and density radial profiles. We neglect the small Tedependence
in f(x,Te) forthis analysis andincorporate f(x,Te=10 keV)into
the ASZfactor.
For the de-projection analysis, the X-ray surface brightness
profile can be written as (e.g. Yoshikawa & Suto 1999):
4π(1 + z)4
We use the APEC code (Smith et al. 2001) to compute the
cooling function, Λ(Te(r)) for Abell 2163, assuming an abun-
dance value of 0.4Z⊙, where Z⊙is the solar metallicity. This also
includes the absorption by the neutral hydrogen of the Galaxy
using a column density of 1.1 × 1021cm−2, as measured by
the L.A.B. survey (Kalberla et al. 2005) at the cluster position.
While the temperature dependence of the cooling function is
thus included in the analysis, it is interesting to note that the
results changes very little when assuming Λ is independent of
Te. As we shall see in section 5.2, however, systematic effects
in the gas density from uncertainties in the metal abundance are
Using Abel's integral equation, equations (8) and (9) can be
inverted to obtain joint radial density and temperature profiles:
f(x,Te) ne(r) Te(r)
√r2− R2
e(r) ΛH(Te(r))
√r2− R2.
Te(r) ne(r) =
√R2− r2;
√R2− r2.
e(r)Λ(Te(r)) = 4(1 + z)4
Following Yoshikawa & Suto (1999), we integrate equations
(10) and (11) numericallyby summing in radial bins from iminto
imax, whereimaxis the indexfor the outermostbin,and imincorre-
sponds to r/DA. We propagatethe errors on the density and tem-
perature profiles by a Monte-Carlo method, the details of which
will be discussed in a future publication (Basu et al. 2009, in
5.1.2. Profile extraction
The SZE profile is derived as a radial average of the data and
errors are estimated using the same method as in H09. In order
to combine the two data sets, the X-ray raw mosaic has been
smoothedto the APEX-SZ resolutionof 1′. In doingso, we have
neglected the effects of the XMM point spread function (PSF)
and its variation over the field since they are negligible com-
pared to the APEX-SZ beam. The X-ray source mask is used to
removethe sub-cluster 8 arcminutes northof Abell 2163,promi-
nent in Figure 3, and the numerousAGN. A count profile is then
extracted from the background subtracted mosaic and corrected
for the local exposure time and unmasked area, thus converting
to surface brightness. The Poisson error bars on the counts pro-
files are re-scaled accordingly. Since the background and source
counts in each annulus are large, the noise can be considered
as Gaussian which justifies the direct background subtraction.
Because of the slight offset between the peaks of the X-ray sur-
face brightness and the SZE temperature decrement, we have
taken the centroid position of the X-ray map to be the common
signal-to-noise ratio of the X-ray map.
5.1.3. Mass estimation method
Using the SZE and X-ray measurements, we can determine the
gas mass and total mass enclosed within a certain radius assum-
ing hydrostatic equilibrium. This can be used to compute the
gas-to-mass ratio as a function of radial distance, or can be com-
binedwiththe weak-lensingdatafora moredirectdetermination
of the gas mass fraction. We show the comparison between the
gas mass fraction values obtained using our non-parametric de-
projection method and the standard isothermal modeling inside
the r500of the cluster.
Computingthegasmass andtotalmass profilesfromisother-
mal β models is straightforward (e.g. LaRoque et al. 2006). The
gas mass is obtained directly from the electron density profile as
Mgas(< r) = 4π µene(0)mpD3
1 +θ2
θ2dθ, (12)
where µeis the mean molecular weight per electron, which we
assume to be equal to 1.17 for cosmic abundance of H and
He. For the non-isothermal analysis, we use the de-projected
electron density profile to compute the gas mass directly as
ρgas(r) = µempne(r).
The total mass, Mtotal, is obtained by solving the hydrostatic
equilibrium (HSE) equation, assuming spherical symmetry, as
Page 10
10M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
Mtotal(< r) = −kBTe(r) r
For isothermal modeling, we use the simple analytic form ob-
tained from the above equation (e.g. Grego et al. 2001)
Mtotal(< r) =3β kBTe
r2+ r2
whereas for non-isothermal modeling we solve equation 13 di-
rectly. The gas mass fraction is in both cases computed as
fgas(< r) = Mgas(< r)/Mtotal(< r).
5.2. Systematics
The dominating source of error in the non-parametric de-
projection analysis comes from uncertainties in the SZE map
at 150 GHz. Intrinsic noise properties in the raw map cause the
uncertainties in the radial bins to be strongly correlated due to
noisestructuresmuchmoreextendedthanthe binwidth.In addi-
tion, the deconvolutionprocess discussed in section 3.3 not only
recovers source signal, but can also amplify noise structures in
the raw map, thus increasing the uncertainties in the radial pro-
file (see Fig. 4). This amplification of noise effectively limits the
range of radii for which we can make meaningful estimates of
the ICM temperature and density.
As already discussed in section 4.4.4, some modes corre-
spondingto large angular scales are irrecoverableby the transfer
function − in particular, no structures more extended than the
path traced by a single bolometer during a scan can be recov-
ered. Although the SZE profile is well constrained within r500,
this inherentfiltering can lead to systematic shifts in temperature
and density at larger radii, where the SZE signal is potentially
Cavaliere, Lapi and Rephaeli (2005) showed that the Abel
deprojection method in itself can lead to biases in the estimated
temperature and density profiles. However, they also found that
this bias is significantly smaller than the statistical uncertainty,
whichtheyoptimisticallyassumed to be1% on the centralvalue.
Other systematic uncertaintiescomefromprimaryCMB sig-
nals, modeling of the X-ray background, and the metal abun-
dance used in computing the X-ray cooling function. We con-
sider each source of systematic uncertainty in what follows. The
results are summarized in table 2. Representative radial scales
are taken from the best-fit NFW model from weak-lensing anal-
ysis of this cluster (Radovich et al. 2008): r2500 = 3.1′and
r500= 7.6′.
5.2.1. The filter function
To address the issue of how irrecoverable signals on large angu-
lar scales in the SZE map affect the temperatureand density pro-
files, we once again carry out a series of simulations (cf. section
4.4.4), passing artificial models through the reduction pipeline.
While in section 4.4 we considered only how the signal was af-
fected by the pipeline in terms of fitting a parametric function
out to a certain radius using the transfer function, we now also
have to consider systematic effects from using the transfer func-
tion to deconvolve the map rather than to convolve a model (the
latter is much more straightforward). Lacking a more complete
model of the cluster emission, we again use spherical β mod-
els, and vary the best-fit parameters from section 4 within their
1σ errors to test for stability. After passing the models through
the pipeline,we deconvolvethem using the transfer functionand
compare the resulting profiles with the input models. While the
systematic errors estimated from this method are comparable to
the random errors on the SZE profile inside r500, the signal is
systematically lowered by as much as 40% of the input signal at
r200.Note,however,thatat anyradiusconsideredin ouranalysis,
this systematic effect is small comparedto theintrinsic statistical
error originating in the raw map.
ingful in the context of the isothermal model. They are justi-
fied, however,by the results of section 4, which indicate that this
model indeed provides a very reasonable fit to the data out to
r500. In contrast to what was done in the isothermal analysis, we
do not attempt to correct for this effect since we have no para-
metricmodel.Instead,we treatthe systematicas an addeduncer-
tainty on the SZE profile, and propagatethis uncertaintythrough
the de-projection analysis to estimate the resulting uncertainties
in temperature and density.
5.2.2. Primary CMB
The systematic uncertaintyfromthe primaryCMB signal is esti-
mated using a methodanalogous to that described in section 4.4.
After a set of simulated primary-CMB maps are subtracted from
time stream data and passed through the pipeline reduction, de-
convolution is performed on each map in the set. The different
maps are then passed through the de-projection analysis to es-
timate the impact on the derived quantities. It is found that the
uncertainties are comparable with those of the filter function.
5.2.3. X-ray background and metal abundance
Although the statistical errors on the recovered temperature and
density profiles are clearly dominated by the uncertainty in the
SZE signal, several X-ray systematics have to be considered.
As mentioned in section 3.5, the background model can
have a significant impact on the X-ray surface brightness at
large radii. To quantify this further, we fix all the parameters
of the background model to their best fit value, and allow for an
overall change in normalization in the instrumental and cosmic
background. Identifying the Cash statistic with a χ2distribution
(valid in the large number limit), we derive a 1σ uncertainty for
this normalizationfactor of +1.9%/-1.2%.At r500, this translates
into a 3% uncertainty in the temperature profile and 1% for the
electron density, much below the statistical errors.
Our assumption of a fixed metal abundanceis anotherpoten-
tial source of systematics. Line emission is indeed preeminentin
thesoft energybandandthis couldresult ina significantlydiffer-
ent value of the cooling function required for our de-projection
analysis.We havethusinvestigatedtheimpactofa globalchange
in metallicity in the range 0.2 to 0.8Z⊙. These values correspond
by Snowdenet al. (2008)fromX-rayspectroscopy,yet they only
change our results by up to few per cent, again smaller than the
statistical uncertainties. The small systematic uncertainties are
a direct consequence of the high temperatures measured for this
cluster; line emission at soft energiesis indeed muchreducedfor
plasma hotter than ∼2 keV in which more energetic transitions
are favored.
Page 11
M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect 11
Table 2. Systematic effects in the de-projected temperature and
density profiles. Statistical errors are indicated for comparison.
Source of
Effect on Te
Effect on ne
Primary CMB
Filter function (SZE map)
X-ray background
Metal abundance
Total systematica
aAdded in quadrature
5.3. Results of the non-isothermal modeling
5.3.1. Density and temperature profiles
The radial profiles of the ICM density and temperature,obtained
from equations 10 and 11, are shown in Figure 5. The density
profileshowsverylittle deviationfromanisothermalβmodelin-
side r500(roughly1500kpc),which is expectedsince the density
values are mostly constrained by the X-ray surface brightness
map. In the [0.5-2] keV energy band the X-ray surface bright-
ness depends weakly on the gas temperature; for this reason the
de-projected density profile using this band has a weak depen-
dence on temperature variations. Inside r500the temperature can
be fit with a constant (i.e. isothermal) value, at 10.4 ± 1.4 keV,
marked by the horizontal dashed line in Fig.5.
Since no "de-projected" temperature profile for Abell 2163
from X-ray spectroscopic measurements is available in the lit-
erature, we compute the mean weighted value of the gas tem-
perature along the line of sight to compare our results with the
published X-ray temperature values. The projected gas temper-
ature is computed as Tproj≡
de-projected gas temperature obtained from Abel inversion, and
W is the weight function. As expected, the effect of projection
is small compared to the errors in our temperature profile. We
compare two different weighing schemes: the standard emission
weightwithW = n2Λ(T),andtheweighingfora"spectroscopic-
like" temperature as discussed by Mazzotta et al. (2004), us-
ing W = n2T−3/4. The difference between these two weighing
schemes is negligible, as can be expected from the slowly vary-
ing temperature profile of A2163 which shows no strong non-
isothermal features.
In Figure 6 we compare the emission-weighted temperature
with published spectroscopic measurements from XMM-Newton
and Chandra observations. The XMM-Newton temperature pro-
file indicates a drop in temperature in the central region, which
maybe the remnantof the coldcoreof the originalmoremassive
cluster in this merging system. Gas temperatures derived from
the APEX-SZ measurement are consistent with this feature. In
the outskirts, gradually decreasing temperatures with incresing
radii have been observed for relaxed clusters (e.g. Pratt et al.
2007), and is expected from both theory (e.g. Frenk et al. 1999)
and numerical simulations of cluster models (e.g. Roncarelli et
al. 2006, Hallman et al. 2007). Although the large uncertainties
in the present temperature profile beyond r500do not allow any
conclusions as to a decrease in temperature at large radii, the
data are fully consistent with such a trend.
WTdV /
WdV, where T is the
Fig.5. De-projected radial density and temperature profiles of
Abell 2163 from X-ray (XMM-Newton) and APEX-SZ data.
Top: De-projected radial density profile (1σ confidence region).
Thedashedlineis theX-rayderivedsphericalβ profile(β = 0.64
and θc= 91′′), normalizedto the derivedcentral electron density
value. Bottom: De-projected temperature profile with 1σ uncer-
tainties. The horizontal dashed line shows the best-fit isothermal
value of 10.4 ± 1.4 keV within r500(∼7.6′). Vertical arrows in
both plots mark the estimated values of r200and r500.
5.3.2. Gas mass and total mass
The results of the mass analysis are shown in Figure 7. We have
used median smoothing to the temperature and density profiles
before computing their derivatives, and limited this analysis to
within r500(approximately 1500 kpc) to avoid the large uncer-
tainties at the outer radii. The errors in the total mass and gas
mass fraction profiles reflect the combined random and system-
atic errors in our analysis. We find that the cumulative mass pro-
file obtained under the assumption of HSE with spherical sym-
metry is in good agreement with the total mass obtained from
weaklensing (Squireset al. 2007).The presentanalysis provides
a better constraint on the total mass profile if the assumption of
HSE is valid. The cumulative fgasvalues near the cluster cen-
ter obtained from the non-parametric modeling are systemati-
cally higher than the isothermal β-model predictions. The drop
to zero of the gas mass fraction at small radii is a well-known
artefact of the isothermal β−modeling of cluster ICM, and our
non-parametric profile may be indicative of the actual ratio be-
tween gas and total gravitational matter near the cluster center.
At a radiusof 1Mpcand beyond,the fgasvaluesfrombothmeth-
ods agree within 1σ.
Page 12
12M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
0 500 100015002000
r (kpc)
kT (keV)
02468 1012
Ang. distance (arcmin)
Fig.6. Comparison of the projected radial temperature pro-
file for Abell 2163 with spectroscopic X-ray measurements.
The shaded region shows the emission-weighted temperature
computed from the de-projected temperature and density pro-
files. The squares and crosses are X-ray spectroscopic measure-
ments from Chandra (Markevitch & Vikhlinin 2001) and XMM-
Newton (Snowden et al. 2008), respectively.
The resulting non-parametric gas mass fraction profile for
Abell 2163 is close to the universal baryon fraction obtained
from the WMAP 5-year data (Dunkley et al. 2009), and is also
consistentwiththeX-rayanalysisofSquiresetal. (1997)forthis
cluster. The joint SZE/X-ray analysis of the gas fraction in clus-
ters using OVRO/BIMA data (LaRoque et al. 2006) also yields
a value of fgasin the range 0.15 − 0.16 for this cluster, using a
non-isothermal double β-model. The latter measurement is lim-
ited to within r2500, and at this radius the SZE-only isothermal
value is approximately 30% lower than the double β-model re-
sult, consistent with the difference found in our analysis.
It should be noted that the plotted mass and gas mass frac-
tions are cumulative functions, and hence their values in the
outerbins arecorrelatedwith the data inbins closer to thecenter.
Furthermore, the errors in fgasare derived from the errors in the
total mass and gas mass profiles, which are not independent.For
these reasons, the errors in fgasare also correlated.
6. Constraints from the SZE spectrum
TocomparetheSZE decrement/incrementvaluesat differentfre-
quencies, we write them in terms of the relative change to the
background CMB intensity,
∆I = I0h(x) Ωbeam
where x ≡ hν/kTCMB, I0≡ 2(kTCMB)3/(hc)2, Ωbeamis the beam
equivalent solid angle in steradians, and h(x) relates the fre-
quency dependence of the SZE expressed in temperature and in
intensity as
h(x) =
(ex− 1)2.
The total change of intensity is written as the sum of the thermal
and kinematic components of the SZE as
∆IT= I0y h(x) f(x,Te) (17)
300600 1200
r (kpc)
Mtot(<r) (Msolar)
r (kpc)
gas mass fraction, fgas(<r)
Fig.7. Top: Gas mass and total mass in Abell 2163 within r500
(∼1500 kpc), obtained from the de-projected density and tem-
perature profiles. The shaded region shows the total mass within
68% confidence levels. The dashed line is the gas mass, con-
strained primarily from the X-ray data. The square boxes with
error bars are the weak-lensing mass profile from Squires et
al. (1997). Bottom: The gas mass fraction obtained from the
isothermal analysis (solid line) and from the non-parametric de-
projection (shaded region, 68% CL). The triangles with error
bars are the results from the X-ray analysis of Squires et al.
(1997), and the horizontal dot-dashed line represents the cos-
mic baryon fraction from the WMAP 5-year result (Dunkley et
al. 2009).
∆IK= −I0y h(x) (mec2/kBTe)vr
with vrthe radial (line-of-sight)peculiar velocity, which is posi-
tive for a receding cluster.
Relativistic corrections to third order in kBTe/mec2are in-
cludedin f(x,Te)accordingtoSazonov&Sunyaev(1998)(Note
that the quantity h(x) f(x,Te) is often denoted g(x,Te) in the
literature). Higher order relativistic corrections are negligible
given the precision of the current measurements. For the pur-
pose of fitting the SZE spectrum, the Comptonization parameter
y (defined in equation 3) is parameterized in terms of its central
value y0. This allows a simple model where the finite resolutions
of different experiments are accounted for. All the spectral data
are obtained with a radial fit using spherical β models, and ac-
counting for beam dilution. For APEX-SZ and LABOCA, we
use the central decrement/increment values, corrected for dust
Page 13
M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect13
Table 3. SZE decrement/increment measurements used for the
spectral fit.
Wavelength (mm)
∆I (MJy sr−1)
1LaRoque et al. (2002)
2Holzapfel et al. (1997)
3dust-corrected intensities from LaRoque et al. (2002)
4calibration corrected according to Hill et al. (2009)
contamination, derived in section 4. The data used for the fit to
the SZE spectrum are given in Table 3.
Due to the degeneracies between velocity, temperature and
Comptonization, the present data is not sufficient for a simulta-
neous constraint of all three parameters. Instead, we fix the ICM
temperature to 10.4 keV from the joint X-ray and SZE analysis
of section 5, and perform a least squares fit in y0and vr. We also
fit these parameters using alternative values of the temperature
in the range 8-14 keV.
To estimate the errors in the fitted parameters, we perform a
Monte Carlo simulation, in which 10,000 artificial data sets are
created from the actual spectral data, adding random Gaussian
offsets with the amplitude of the statistical noise at each fre-
quency. To model the effect of the systematics, we also add
random offsets from the most important systematic components
fromsection 4.4, with the propercorrelationsbetween the differ-
ent frequencies taken into account. Dust and primary CMB sig-
nals are scaled to the estimated levels derived in section 4 at 150
and 345 GHz and to the levels derived by LaRoque et al. (2002)
at the other frequencies. To account for primary calibration un-
certainties, we assume a 5% calibration uncertainty across the
The resulting error estimates, including systematics, are
shown in Figure 8. The fitted radial velocity of the cluster is
consistent with zero, in agreement with and marginally im-
proving the constraints of LaRoque et al. Specifically, we find
vr= −140 ± 460 km/s and y0= 3.42 ± 0.32 × 10−4, excluding
systematic effects.Thefit is dominatedbyrandomnoise;we find
that includingthe systematic errorsin the modelingincreases the
error in y0by 12% and in vrby 18%. The SZE spectra resulting
from the various fits are indicated in Figure 9.
7. Conclusions
1. We present SZE maps of the galaxy cluster Abell 2163 at
two frequencies, showing the SZE decrement at 150 GHz
the SZE increment at 345 GHz from observations with the
LABOCA bolometer camera. The 345 GHz measurement is
the highest resolution SZE image for this cluster to date, and
the first large-area(> 10′) imagingof a galaxycluster at sub-
mm wavelengths.
2. An isothermal modeling of the SZE yields results consistent
with the X-ray derived isothermal model fits, implying that
of spherical symmetry, are well represented by such models.
3. UsingtheAPEX-SZmapinconjunctionwithXMM-Newton
X-ray data we derive the (de-projected) radial density and
Fig.8. Constraints in the vr− y0parameter space of Abell 2163
with priors on the ICM temperature, including systematic un-
certainties. Top: solid contours indicate the 68% and 95% confi-
dence regions using all available data and assuming kTe= 10.4
keV. The dashed contours correspond to excluding the present
(APEX-SZ and LABOCA) measurements. Bottom: 68% confi-
dence regions for a range of ICM temperatures (indicated) using
all available data.
temperature profile of the ICM under the assumption of
spherical symmetry. The projected gas temperature profile
is found to be fully consistent with previous X-ray spectro-
scopic measurements of Markevitch & Vikhlinin (2001) us-
ing Chandra data, and Snowden et al. (2008) using XMM-
Newton data.
4. The total mass profile of the cluster is obtained under the
assumption of hydrostatic equilibrium. The resulting profile
agrees well with the weak-lensing mass profiles from previ-
ous works (Squires et al. 1997, Radovich et al. 2008), and
extends the profile out to r500.
5. The gas mass fraction of the ICM obtained from our non-
parametric analysis are consistent with the previous X-ray
mesurements(Squires et al. 1997)and SZE/X-ray joint anal-
ysis with double β-model (LaRoque et al. 2006). We do not
see any significant trend for increasing ICM baryonic frac-
tion from r2500to r500of the cluster.
6. Using isothermal fits to the LABOCA and APEX-SZ mea-
surements,we constrainthe line-of-sightpeculiarvelocityof
the cluster and the central optical depth to inverse Compton
scattering, using the temperature obtained from the de-
projection analysis. We find a peculiar velocity vr= −140 ±
y0= 3.42± 0.32 × 10−4.
Page 14
14 M. Nord et al.: Multi-frequency imaging of the galaxy cluster Abell 2163 using the Sunyaev-Zel'dovich Effect
Fig.9. SZE spectrum of Abell 2163 (points) and best-fit models
usingdifferentpriorsontheICM temperature:8keV (solidline),
10 keV (long-dashed line), 12 keV (short-dashed line) and 14
keV (dotted line).
Acknowledgements. We thank the APEX staff for their unfailing support dur-
ing the APEX-SZ and LABOCA observations. We thank Wilhelm Altenhoff for
fruitful discussions on the calibration of the millimeter data, and Fred Schuller
for helping with the LABOCA data taking. This work has been partially sup-
ported by the DFG Priority Program 1177. MN acknowledges support for this
research through a stipend from the International Max Planck Research School
(IMPRS) for Radio and Infrared Astronomy at the Universities of Bonn and
Cologne. FP acknowledges support from the DfG Transregio Programme TR33.
NWH acknowedges support from an Alfred P. Sloan Research Fellowship.
APEX is a collaboration between the Max-Planck-Institut f¨ ur Radioastronomie,
the European Southern Observatory, and the Onsala Space Observatory. APEX-
SZis funded bythe National Science Foundation under Grant No. AST-0138348.
XMM-Newton is an ESA science mission with instruments and contributions di-
rectly funded by ESA Member States and the USA (NASA). The XMM-Newton
project is supported in Germany by the Bundesministerium f¨ ur Wirtschaft und
Technologie/Deutsches Zentrum f¨ ur Luft- und Raumfahrt (BMWI/DLR, FKZ 50
OX 0001), the Max-Planck Society and the Heidenhain-Stiftung.
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Harbinger Winery wins gold at international wine competition
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Harbinger's 2010 Malbec won a silver medal and its 2009 Barbera a bronze at the Sunset competition, entered by nearly 3,000 wineries from around the world.
Last year Harbinger's 2008 El Jefe and 2008 Barbera both took gold medals. The 2010 Malbec also won a gold medal at The Great Northwest Wine Competition recently.
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Mevorach, Carmel and Shalev, Lilach and Allen, Harriet A. and Humphreys, Glyn W. (2009) The left intraparietal sulcus modulates the selection of low salient stimuli. Journal of cognitive neuroscience, 21 (2). pp. 303-15. ISSN 0898-929X
| URL of Published Version: http://www.mitpressjournals.org/doi/full/10.1162/jocn.2009.21044 Identification Number/DOI: 10.1162/jocn.2009.21044 Neuropsychological and functional imaging studies have suggested a general right hemisphere advantage for processing global visual information and a left hemisphere advantage for processing local information. In contrast, a recent transcranial magnetic stimulation study [Mevorach, C., Humphreys, G. W., & Shalev, L. Opposite biases in salience-based selection for the left and right posterior parietal cortex. Nature Neuroscience, 9, 740-742, 2006b] demonstrated that functional lateralization of selection in the parietal cortices on the basis of the relative salience of stimuli might provide an alternative explanation for previous results. In the present study, we applied a whole-brain analysis of the functional magnetic resonance signal when participants responded to either the local or the global levels of hierarchical figures. The task (respond to local or global) was crossed with the saliency of the target level (local salient, global salient) to provide, for the first time, a direct contrast between brain activation related to the stimulus level and that related to relative saliency. We found evidence for lateralization of salience-based selection but not for selection based on the level of processing. Activation along the left intraparietal sulcus (IPS) was found when a low saliency stimulus had to be selected irrespective of its level. A control task showed that this was not simply an effect of task difficulty. The data suggest a specific role for regions along the left IPS in salience-based selection, supporting the argument that previous reports of lateralized responses to local and global stimuli were contaminated by effects of saliency. |
Type of Work: | Article |
Date: | February 2009 (Publication) |
School/Faculty: | Colleges (2008 onwards) > College of Life & Environmental Sciences |
Department: | School of Psychology |
Keywords: | POSTERIOR PARIETAL CORTEX; TRANSCRANIAL MAGNETIC STIMULATION; VISUAL-ATTENTION; HEMISPHERIC ASYMMETRIES; SPATIAL-FREQUENCY; MOTOR ATTENTION; RHESUS-MONKEY; BRAIN IMAGES; FRONTAL-LOBE; FMRI |
Subjects: | RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry BF Psychology |
Institution: | University of Birmingham |
Copyright Holders: | Massachusetts Institute of Technology |
ID Code: | 687 |
Refereed: | YES |
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The Great Escape Rumble Winners Announcement
9 24 Share TweetFor this rumble, you don't need to be disappointed if you hit and missed your subject! Because that was exactly what we were looking for: your finest escapism photographs! Read more to know the winners for this Houdini tribute!
A couple of months ago, we paid tribute to the world's greatest escape artist, *Harry Houdini*, so we thought of asking your own versions of escapism through film photographs. It was not surprising that we had so much fun picking out the best hits-and-misses from you! Seeing perfect smiles with cropped heads really cracked us up.
Anyway, without further delay, here are winners of The Great Escape Rumble in no specific order. Each of you gets 5 Piggies and a special award badge to your LomoHomes!
Congratulations to all the winners! And thank you, everyone, for your participation. Till the next competition!
written by nyebe on 2012-05-12 in #competitions #winners #winners-announcements #rumbles #weekly-tributes #harry-houdini #harry-houdini-week


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St. Peter's Cathedral
This Renaissance Gothic architectural masterpiece has a 222 ft. tall bell tower. Tours avalaible.
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Join the group at this small intimate club featuring performers from St. Louis and the local area.
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The Thomas Kinkade Gallery of Belleville is full of beautiful works by Thomas Kinkade.
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Visitors are invited to walk through this home, considered to be the oldest Greek Revival-style home in Illinois.
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Over 350 permanent works, including a beautifully landscaped and sculptured garden, are on display.
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The historic theatre features first-run movies, organ concerts, puppet shows, and other special events. Tours are available by appointment.
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Limelight Players
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Labor & Industry Museum
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Skyview Drive-In
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National Shrine of Our Lady of the Snows
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Clinton County Showcase
The Showcase performs at the historic Avon Theatre. Call for a schedule of plays.
General Dean Suspension Bridge
Located just outside the city of Carlyle, this historic 130-year-old bridge is one of the oldest suspension bridges in the area. The original bridge served as a crossing over the Kaskaskia River.
Clinton County Historical Museum
This building was the former home of Judge Sidney Breese, who came to Illinois from New York. He studied law here and became Assistant Secretary of the State of Illinois.
Centralia Area Historical Museum
Artifacts, pictures of coal mining, railroading, business, farming in and around Centralia. A work in progress by the Centralia Area Historical Society to preserve the past of Marion County.
Centralia Historical Society Museum
Centerpieces of the collection are newspapers and memorabilia from the coal mining days with tributes to railroad history.
Centralia Illinois Downtown Theatre
This former vaudeville and movie theatre has been restored to its former glory. The Playbill for the 2008 season includes Chapter 6, an acapella group that started at Milliken University in Decatur, IL and now tours worldwide and the touring company of Second City in Chicago. Don't miss the excitement.
Civil War Monument at the Veterans' Memorial
This monument honors generations of soliders who sacrificed their lives for their country.
Bond County One Room School Museum
This museum is a living monument to the more than 72 one-story schools throughout the nation that served to educate children and host community gatherings.
Ten Talents Gallery and Gifts
Ten Talents Gallery features handmade, individual, and unique items by Illinois artists. We offer such items as jewelry, watercolors, ceramics, wood carvings, and much more.
American Farm Heritage Museum
Farm implements, tools, tractors, and other equipment are featured that date back 100 years. The museum is open for special events including the Outhouse Festival in the fall.


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About Melissa Schroeder
Since she was born to an Air Force family in the Army hospital, Melissa Schroeder has always been a little screwy. Years of watching Monty Python and her strange family warped her even more. She found romance after accidentally picking up a Linda Howard book–and then read over 300 romances in one year. Because of her upbringing, she vowed never to marry military. Alas, fate always has her way with mortals. Melissa is married to a major in the AF and is raising her own military brats. She is happy to report that they are finally living where the bugs die in the winter.
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The use of marijuana is associated with a marked increase in the risk of being involved in severe trauma particularly motor vehicle collisions. In 2009, for instance, marijuana use was a contributing factor in more than 460,000 emergency department visits in the United States.
But we also know that cannabis is potentially neuroprotective. Previous studies have found that tetrahydrocannabinol (THC), the active ingredient in marijuana, may have beneficial effects in certain types of neurodegenerative processes, like Alzheimer's and Huntington's disease. In addition, previous studies indicate THC may protect the brain in animal models of neurologic injury. However, clinical trials of a synthetic THC derivative were not ultimately associated with an increase in survival in patients with traumatic brain injury. Since overall findings were mixed, we hypothesized that use of the "native" form of THC could be associated with an increase in survival in patients with traumatic brain injury.
Continue reading "Can Pot Protect the Brain After Injury? A New Study Says It Can"
Filed Under: THCB
Tagged: alcohol, critical care, Los Angeles Biomedical Research Institute, Marijuana, Neurologic injury, THC, Trauma, Wellness Oct 3, 2014


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Angelina - Unregistered February 03, 2013 3:58 PM Ron r u sure its Seb Vettel? Seb alwayts says that he doesn't have a twitter and fb account. 2 agree 6 disagree
ricmcl - Unregistered February 03, 2013 4:15 PM The car that will be on the grid in Melbourne will bear little resemblance to what they are showing here. Probably 10 different front wings etc, etc. 0 agree 1 disagree
rob01 February 03, 2013 4:32 PM Angie, Yes i am sure. I think Seb got it after Bernie said he was missing a personality. Reply Report abuse 6 agree 5 disagree
Angelina - Unregistered February 03, 2013 4:39 PM robAnd he has just a few posts betn 17th april 2011 & 25th april 2011 and nothing afterwards. LOL! 3 agree 5 disagree
Ptolomy - Unregistered February 03, 2013 7:38 PM Sebastian is not your average idiot with a Facebook and a Twitter account.He doesn't want to tell everyone what he has for breakfast and such. 3 agree 5 disagree
James - Unregistered February 03, 2013 7:48 PM I'd love to know what Sebastian eats for breakfast. Probably Red Bull cereal, shaped like little RB6/7/8s, a can of Red Bull served at championship winning controlled temperature of 7 degrees, from an RB cooler. Then he showers in Red Bull, and sleeps in an Adrian Newey designed blanket. Admittedly, some of these things he posted in 2011. 2 agree 0 disagree
JJJ - Unregistered February 04, 2013 2:29 AM Livery looks garish but I've always found that to be true about the RBR livery, I wish they'd go to the mid 90s Sauber livery with Red Bull sponsoring which looked a lot cleaner (the dark blue one).That said I think this sparkling skittles promotion is going to look pretty modern and cool under the lights at Singapore and Abu Dhabi which is probably what they had in mind...at Spa, Suzuka or Silverstone though...not so much. 0 agree 1 disagree
Cheaters - Unregistered February 04, 2013 6:48 AM Hamilton should be riding this pimp-mobile. It looks like a boom-boom car! 1 agree 1 disagree
Wolfy35 February 04, 2013 2:11 PM Oh well that ends the optimism until then that all of this years cars would be free of the eyesore that is the stepped nose. Reply Report abuse 0 agree 0 disagree
RickyP - Unregistered February 04, 2013 4:01 PM I think the point was that just because Sebastian has a Twitter account and he took a photo of his car, doesn't mean he'll be posting photos of it. Until he gets say so from the team at least. 0 agree 0 disagree


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Ibex Europa Jacket
Where to Buy
Manufacturer's Description
Visit Ibex's Europa Jacket page.
Retailers' Descriptions
Here's what other sites are saying:
Made from soft, warm Austrian Loden, the Ibex Europa Jacket is a smart choice for chilly season strolls. The stylish and durable wool protect you from the weather while maintaining a professional look you can wear to the office or to dinner.-- Made in the USA-- Regular Fit-- Mid-hip length-- Full front zip-- Zippered hand pockets-- Contrast color Pez fabric on inside collar-- Hand wash or Dry clean
- OMCgear
Zip up the super warm Ibex Men's Europa Jacket and head downtown to your favorite coffee shop on a snowy day. Ibex water-processed this completely wool jacket so it can handle light rain and snow. The mid-hip length and relaxed fit of the Europa Jacket makes layering under it a cinch, so you can walk the few miles downtown in warmth.
- Backcountry.com
Active lifestyle clothing at its best, the Ibex Men's Europa Jacket offers handsome good looks and practical performance for day to day wear. The attractive appearance is highlighted by the exposed swiss zippers and texture of the dense knit Loden wool, which looks course but has a soft hand. Once on, the Ibex Men's Europa Jacket feels incredibly comfortable. It's warm as expected, but it's also surprisingly comfortable in wide ranging temperatures, thanks to the Loden wool's natural temperature regulating properties. The Ibex Men's Europa Jacket also offers a fair amount of stretch, not as much as a pair of running tights, but enough to make a difference when a full range of motion is needed. For protection from rain and snow showers, the Ibex Europa Jacket stands up to the task. The Loden wool is prepared using a cold water process that leaves the natural, water and stain repellant lanolin intact.
- Altrec Outdoors


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