Issue |
A&A
Volume 518, July-August 2010
Herschel: the first science highlights
|
|
---|---|---|
Article Number | L12 | |
Number of page(s) | 5 | |
Section | Letters | |
DOI | https://doi.org/10.1051/0004-6361/201014696 | |
Published online | 16 July 2010 |
Herschel: the first science highlights
LETTER TO THE EDITOR
The Herschel Lensing Survey (HLS): Overview
,![[*]](/icons/foot_motif.png)
E. Egami1 -
M. Rex1 -
T. D. Rawle1 -
P. G. Pérez-González2,1 -
J. Richard3 -
J.-P. Kneib4 -
D. Schaerer5,6 -
B. Altieri7 -
I. Valtchanov7 -
A. W. Blain8 -
D. Fadda9 -
M. Zemcov8,10 -
J. J. Bock8,10 -
F. Boone6,11 -
C. R. Bridge8 -
B. Clement4 -
F. Combes11 -
M. Dessauges-Zavadsky5
-
C. D. Dowell8,10 -
O. Ilbert4 -
R. J. Ivison12,13 -
M. Jauzac4 -
D. Lutz14 -
L. Metcalfe7 -
A. Omont15 -
R. Pelló6 -
M. J. Pereira1 -
G. H. Rieke1 -
G. Rodighiero16 -
I. Smail3 -
G. P. Smith17 -
G. Tramoy4 -
G. L. Walth1 -
P. van der Werf18 -
M. W. Werner10
1 - Steward Observatory, University of Arizona,
933 N. Cherry Ave, Tucson, AZ 85721, USA
2 -
Departamento de Astrofísica, Facultad de
CC. Físicas, Universidad Complutense de Madrid, 28040
Madrid, Spain
3 -
Institute for Computational Cosmology, Department of Physics,
Durham University, South Road, Durham DH1 3LE, UK
4 -
Laboratoire d'Astrophysique de Marseille, CNRS -
Université Aix-Marseille, 38 rue Frédéric
Joliot-Curie, 13388 Marseille Cedex 13, France
5 -
Geneva Observatory, University of Geneva, 51, Ch. des
Maillettes, 1290 Versoix, Switzerland
6 -
Laboratoire d'Astrophysique de Toulouse-Tarbes,
Université de Toulouse, CNRS, 14 Av. Edouard Belin, 31400
Toulouse, France
7 -
Herschel Science Centre, ESAC, ESA, PO Box 78, Villanueva de
la Cañada, 28691 Madrid, Spain
8 -
California Institute of Technology, Pasadena, CA 91125,
USA
9 -
NASA Herschel Science Center, California Institute of
Technology, MS 100-22, Pasadena, CA 91125, USA
10 -
Jet Propulsion Laboratory, Pasadena, CA 91109, USA
11 -
Observatoire de Paris, LERMA, 61 Av. de l'Observatoire, 75014
Paris, France
12 -
UK Astronomy Technology Centre, Science and Technology
Facilities Council, Royal Observatory, Blackford Hill,
Edinburgh EH9 3HJ, UK
13 -
Institute for Astronomy, University of Edinburgh, Blackford
Hill, Edinburgh EH9 3HJ, UK
14 -
Max-Planck-Institut für extraterrestrische Physik,
Postfach 1312, 85741 Garching, Germany
15 -
Institut d'Astrophysique de Paris, CNRS and Université
Pierre et Marie Curie, 98bis Boulevard Arago, 75014 Paris,
France
16 -
Department of Astronomy, University of Padova,
Vicolo dell'Osservatorio 3, 35122 Padova, Italy
17 -
School of Physics and Astronomy, University of Birmingham,
Edgbaston, Birmingham, B15 2TT, UK
18 -
Sterrewacht Leiden, Leiden University, PO Box 9513, 2300 RA
Leiden, the Netherlands
Received 1 April 2010 / Accepted 19 May 2010
Abstract
The Herschel Lensing Survey (HLS) will conduct deep
PACS and SPIRE imaging of 40 massive clusters of galaxies.
The strong gravitational lensing power of these clusters will
enable us to penetrate through the confusion noise, which sets the
ultimate limit on our ability to probe the Universe with Herschel. Here we present an overview of our survey and a
summary of the major results from our science demonstration phase
(SDP) observations of the Bullet cluster (z=0.297). The SDP
data are rich and allow us to study not only the background
high-redshift galaxies (e.g., strongly lensed and distorted
galaxies at z=2.8 and 3.2) but also the properties of
cluster-member galaxies. Our preliminary analysis shows a great
diversity of far-infrared/submillimeter spectral energy
distributions (SEDs), indicating that we have much to learn with
Herschel about the properties of galaxy SEDs. We have also
detected the Sunyaev-Zel'dovich (SZ) effect increment with the
SPIRE data. The success of this SDP program demonstrates the
great potential of the Herschel Lensing Survey to produce
exciting results in a variety of science areas.
Key words: infrared: galaxies - submillimeter: galaxies - galaxies: evolution - galaxies: high-redshift - galaxies: clusters: general
1 Introduction
With the successful launch and commissioning of the ESA's Herschel Space Observatory (Pilbratt et al. 2010), we are again on the
verge of making great new discoveries. Following the breakthrough
submillimeter/millimeter observations with SCUBA and MAMBO
(cf., Blain et al. 2002), deep MIPS 24 m observations carried out
by the Spitzer Space Observatory have enabled us to trace the
evolution of infrared-luminous galaxies up to
3-4
(e.g., Pérez-González et al. 2005; Le Floc'h et al. 2005). However, the validity of all
these Spitzer-based results rests on the assumption that the
total infrared luminosities of high-redshift infrared galaxies can be
estimated accurately by sampling their rest-frame mid-infrared
emission (e.g., the MIPS 24
m band samples the rest-frame 8
m
emission at z=2). Indeed, some Spitzer results have already
questioned this assumption, suggesting that the use of local galaxy
spectral energy distribution (SED) templates may lead to
overestimating the total infrared luminosities of high-redshift
galaxies (e.g., Rigby et al. 2008; Papovich et al. 2007). Herschel will
allow us to measure the total infrared luminosities of a large number
of high-redshift galaxies directly for the first time.
With Herschel, confusion noise produced by a sea of blended faint galaxies sets the ultimate limit on how deeply we can probe the Universe. Once the source confusion sets in, it is no longer possible to improve the detection limit by integrating longer. This limitation is especially severe for SPIRE, which reaches the confusion limit quickly.
To penetrate through the confusion limit, gravitational lensing by
massive galaxy clusters offers a very powerful and yet cheap solution
(e.g., Blain 1997). Magnification factors of 2-4
are
quite common in the cluster core regions, and when a background source
is strongly lensed (i.e., multiply imaged), magnification factors can
reach 10
-30
or more. Note that a magnification
factor of 10
corresponds to a factor of 100
saving in
observing time when the sensitivity is background-limited. Therefore,
a fairly short-integration image of a cluster core region would often
reveal sources that are well below the detection limit of an
ultra-deep blank-field image. This method was for example employed
for the first SCUBA observations of the high-redshift Universe, which
resulted in the identification of the substantial population of
infrared-luminous galaxies at z>1 (Smail et al. 1997).
The use of gravitational lensing is especially powerful at infrared/submillimeter wavelengths. This is because cluster cores are dominated by early-type galaxies, which usually emit little at these wavelengths. Therefore infrared/submillimeter sources detected in cluster cores are often background galaxies. In other words, when observed at these wavelengths, massive cluster cores virtually act as a transparent lens. Lensing studies in the infrared/submillimeter also benefit from the steep galaxy counts at these wavelengths.
These types of lensing surveys, however, have one limitation: the small number of strongly lensed galaxies observed per cluster. Although a large number of massive clusters have been targeted by ground-based submillimeter/millimeter observations (e.g., Smail et al. 2002; Knudsen et al. 2008; Chapman et al. 2002), the number of strongly lensed (i.e., multiply imaged) galaxies discovered in these surveys remains small: for example, the z=2.5 galaxy in Abell 2218 (Kneib et al. 2004), the z=2.9 galaxy in MS0451.6-0305 (Borys et al. 2004), the z=2.8 galaxy in the Bullet cluster (Gonzalez et al. 2009; Johansson et al. 2010; Wilson et al. 2008; Rex et al. 2009), and most recently the exceptionally bright z=2.32 galaxy in MACSJ2135-0102 (Swinbank et al. 2010). Based on these observations, we empirically estimate the rate of finding these strongly lensed infrared/submillimeter galaxies to be roughly 1 in 10 with the sensitivity of ground submillimeter observations (e.g., SCUBA, LABOCA). Therefore many tens of clusters need to be observed to study a significant number of strongly lensed galaxies.
2 The Herschel Lensing Survey (HLS)
As a Herschel open-time key program, we are conducting exactly
such a large lensing survey, targeting 40 massive clusters of
galaxies (``The Herschel Lensing Survey (HLS)'', PI - Egami, 292.3 h). Together with the PACS and SPIRE Guaranteed-Time teams, which
will observe 10 clusters (Altieri et al. 2010; Blain et al., in prep.), we will obtain deep images with PACS (Poglitsch et al. 2010) at 100 and 160
m and SPIRE (Griffin et al. 2010) at 250, 350, and 500
m for a sample of
50 massive clusters as a legacy of the Herschel mission.
Target selection - As the targets of the survey, we chose the
most X-ray-luminous clusters from the ROSAT X-ray all-sky survey
assuming that the most X-ray-luminous clusters are also the most
massive and therefore the most effective gravitational lenses. The
majority of our targets come from the sample of the Local Cluster
Substructure Survey (LoCuSS) (e.g., Smith et al. 2010), which adopts
the following selection criteria: (1)
erg/s,
(2)
0.15<z<0.3, (3)
cm-2, and (4) -
.
In addition, some number of clusters with
spectacular lensed systems were included in the sample. For the
majority of our target clusters, we have well-constrained accurate
mass models, which have been constructed through many years of
intensive imaging/spectroscopic campaigns with HST, Keck, and VLT
telescopes. Other important considerations were the availability of
MIPS 24
m images and accessibility from ALMA for future follow-up
observations although these conditions were not always met.
Observing parameters - Each target cluster is imaged by both
PACS (100 and 160 m) and SPIRE (250, 350, and 500
m). With
PACS we use the scan-map mode with the medium speed (some early data
were taken with the slow speed). The scan leg lengths are 4
,
cross-scan step is 20
,
number of scan legs is 13. Each cluster
is observed twice by orthogonal scan maps (map orientation angles of
45
and 315
)
with 18 repetitions each. The total observing
time is 4.4 h per cluster with an on-source integration time of 1.6 h (1500 s/pixel).
With SPIRE we use the Large Map mode with the nominal speed. The
scan direction was set to scan angles A and B. The length and height
of the map are set to 4,
which in practice will produce a map
of 17
17
.
With 20 repetitions, the total
observing time per cluster is 1.7 h with an on-source integration
time of 0.6 h (17 s/pixel).
Coordinated programs - The Herschel Lensing Survey is
directly coordinated with a few other observing programs. The most
important is the Spitzer/IRAC Lensing Survey (PID 60034; ``The
IRAC Lensing Survey: Achieving JWST Depth with Spitzer'', PI - Egami,
526 h), which is one of the Spitzer Warm-Mission
Exploration Science programs. This program will obtain deep
(5 h/band) Spitzer/IRAC 3.6 and 4.5 m images of
50
massive clusters. By design, its target list is highly overlapped
with that of the HLS. Deep IRAC images will be essential for
identifying optically-faint high-redshift infrared-luminous galaxies
as well as for deriving accurate photometric redshifts. In addition,
roughly half of the HLS clusters are imaged by HST/WFC3 through
two on-going programs (GO 11592: ``Are Low-Luminosity Galaxeis
Responsible for Reionization?'', PI - Kneib, 43 orbits; MCT: ``Through
a Lens, Darkly - New Constraints on the Fundamental Components of the
Cosmos'', PI - Postman, 524 orbits).
The Herschel Lensing Survey is also closely related to two other
Herschel open-time key programs: ``LoCuSS: A Legacy Survey of
Galaxy Clusters at z=0.2'' (Smith et al. 2010) and ``Constraining the
Cold Gas and Dust in Cluster Cooling Flows'' (Edge et al. 2010b,a). The
former will obtain wide (30
30
)
and shallow PACS
100/160
m maps of
30 massive galaxy clusters at
,
many of which are also targeted by the HLS. Note that the HLS
SPIRE maps cover a significant part (the central
17
17
)
of the LoCuSS PACS maps, leading to a
natural collaboration between the two teams. The latter program will
study the brightest cluster galaxies (BCGs) in a dozen cooling-flow
clusters, and the HLS data will provide PACS/SPIRE photometry for a
much larger sample of BCGs.
3 Science demonstration target: the Bullet cluster
In the science demonstration phase (SDP), we observed the Bullet
cluster at z=0.297 (1E0657-56=RXCJ 0658.5-5556). The Bullet
cluster was targeted because (1) there is a strongly lensed bright
submillimeter/millimeter galaxy at z=2.8 (see the Introduction); (2) it has a large amount of ancillary data (see Appendix A); and (3) it
is in the continuous viewing zone of Herschel.
3.1 Data processing
![]() |
Figure 1:
Left - Multi-wavelength imaging data of the Bullet cluster as indicated in each panel (see Appendix A for
references). The contours overlaid on the Chandra and IMACS
images are the weak-lensing mass map from Clowe et al. (2006). The
field of view is |
Open with DEXTER |
Raw Herschel data products were reduced with the common pipeline procedures distributed within the Herschel interactive processing environment (HIPE) (Ott 2010). Deviations from the standard routines are described below.
PACS -- The PACS observations were affected by erroneous
flashes of the calibration lamp at the end of each scan
repetition. These high-intensity spikes in the detector time-streams
were followed by an exponential decay in the signal while the
bolometers re-thermalized. While the spike and a large fraction of the
decay occurred during the slew between repetitions, the bolometers
were not fully stabilized until after the beginning of the next scan,
resulting in a 10 % reduction of usable data.
The 1/f noise drift in the PACS bolometers was removed by a
high-pass filter. Before applying the filter, bright sources (>5)
were masked to prevent Fourier ringing about their
positions. These sources were selected from an unmasked first-pass of
the 160
m map, and the allocated mask size was proportional to
their significance. High-pass filter lengths of 30 and 40 time-stream
frames were used for PACS 100/160
m data respectively. These
lengths were selected to minimize residual 1/f noise in the
resultant maps without clipping power on the scale of the PSF. The
maps incorporate all data observed, while the telescope maintained the
nominal scan speed (including some turnaround data). The final PACS
maps have pixel sizes of 2
and 3
(100/160
m).
SPIRE -- In addition to the nominal scan legs (speed =
30
s-1) we included all turnaround data observed while
the telescope was scanning faster than 0
5 s-1, which
greatly increased the coverage of the outer regions. Low-frequency
drifts in the SPIRE detectors were removed by subtracting the median
value of the nominal scan-speed data from each individual scan leg
independently. The final SPIRE maps have pixel sizes of 6
,
9
,
and 12
(250/350/500
m respectively).
The properties of the processed PACS and SPIRE maps are summarized in Table 1.
Table 1: The HLS Bullet cluster data.
3.2 Overview of the Bullet cluster SDP data
Figure 1 shows the PACS and SPIRE images of the Bullet cluster. Also shown are the Chandra, Magellan/IMACS, Spitzer/IRAC & MIPS 24




We detected two significantly lensed galaxies in the Bullet cluster
field, one at z=2.79 and the other at z=3.24(Rex et al. 2010; Pérez-González et al. 2010). With magnification factors of >54 and 11.3
(Paraficz et al., in prep.) their intrinsic total infrared luminosities
are <
and
.
Figure 1 shows the locations of these two and other
background galaxies studied. Note that only HLS can detect luminous
infrared galaxies (LIRGs;
)
at z > 2-3 in both PACS and SPIRE data.
One major finding of this SDP program is the diversity of
far-infrared/submillimeter SEDs seen with the z =0.3 cluster-member
galaxies, z=0.35 background group galaxies, and higher-redshift
field galaxies behind these two galaxy concentrations (Rex et al. 2010; Rawle et al. 2010). This is shown in Fig. 2, which compares the
total infrared luminosities measured by fitting the Rieke et al. (2009)
SED templates to the observed data points (Measured
)
against
the total infrared luminosity classes originally assigned to these SED
templates (Template
). Although these two luminosities agree
for many of the cluster and background group members, Template
is significantly lower than Measured
for most of
the higher-redshift background galaxies.
What this means is that the
shapes of the infrared/submillimeter SEDs of these galaxies
resemble those of lower-luminosity galaxies in the local Universe.
This result is consistent with the earlier findings by various Spitzer observations (e.g., Rigby et al. 2008; Papovich et al. 2007). This
also implies that these higher-redshift star-forming galaxies have a
larger amount of colder dust compared to the local galaxies with
similar infrared luminosities.
![]() |
Figure 2:
Comparison between the total infrared luminosities measured
by fitting the Rieke et al. (2009) SED templates to the observed data
points (Measured
|
Open with DEXTER |
In the face of this SED difference, the recent finding is surprising
that the total infrared luminosities can be estimated fairly well (at
least up to )
if we use the luminosity-dependent galaxy SED
templates as observed locally (Elbaz et al. 2010). We confirmed this
finding with our Bullet cluster data. Despite this agreement,
however, we also found that the kind of SED mismatch seen in
Fig. 2 clearly exists in the data even at z<1(Rex et al. 2010). This suggests that the good match between the observed
and 24
m-derived total infrared luminosities does not necessarily
mean that the local SED templates provide good fits to the observed
SEDs. A more detailed study of a larger sample is required to resolve
this issue.
Equally interesting is the discovery of cluster/group-member galaxies that show large deviations in the opposite direction (Rawle et al. 2010). In other words, the SEDs of these galaxies resemble those of higher-lumninosity galaxies in the local Universe. These galaxies therefore are likely to have a larger amount of hotter dust and a more pronounced infrared SED peak compared to the local counterparts with similar infrared luminosities. Similar galaxies were also found in other clusters (Smith et al. 2010; Pereira et al. 2010), which possibly suggests that this type of SEDs may be specific to the cluster environment.
Finally, we also report the first detection of the Sunyaev-Zel'dovich
(SZ) effect
increment at 350 and 500 m using the SPIRE data
(Zemcov et al. 2010). The measurements will allow us to assess the
relativistic correction to the SZ effect.
4 Conclusions
The SDP observations of the Bullet cluster clearly demonstrate the great potential of the HLS in a variety of science areas. With the Herschel observations nearly done, HLS is expected to make a rapid progress in the near future. One immediate interest is whether it can find strongly lensed sources that are bright enough to perform spectroscopy with Herschel. Ultimately we will construct a definitive sample of
We thank the following people for providing various data sets/information to us: D. Clowe (Magellan/IMACS images), S. M. Chung and A. H. Gonzalez (IMACS spectroscopic redshifts), J.-G. Cuby (VLT/HAWKI images), D. Johansson, C. Horellou, and the LABOCA team (LABOCA map), and D. Hughes, I. Aretxaga, and the AzTEC team (AzTEC map and far-infrared photometric redshifts). We thank the NASA Herschel Science Center for its excellent user support, and the International Space Science Institute in Berne for their support through the International team 181. EE would like to thank D. Elbaz for communicating his results before publication.This work is based in part on observations made with Herschel, a European Space Agency Cornerstone Mission with significant participation by NASA. Support for this work was provided by NASA through an award issued by JPL/Caltech.
References
- Altieri, B., et al. 2010, A&A, 518, L17 Blain, A. W. 1997, MNRAS, 290, 553 [Google Scholar]
- Blain, A. W., Smail, I., Ivison, R. J., Kneib, J., & Frayer, D. T. 2002, Phys. Rep., 369, 111 [NASA ADS] [CrossRef] [Google Scholar]
- Borys, C., Chapman, S., Donahue, M., et al. 2004, MNRAS, 352, 759 [NASA ADS] [CrossRef] [Google Scholar]
- Chapman, S. C., Scott, D., Borys, C., & Fahlman, G. G. 2002, MNRAS, 330, 92 [NASA ADS] [CrossRef] [Google Scholar]
- Clowe, D., Bradac, M., Gonzalez, A. H., et al. 2006, ApJ, 648, L109 [NASA ADS] [CrossRef] [Google Scholar]
- Edge, A. C., et al. 2010a, A&A, 518, L46 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Edge, A. C., et al. 2010b, A&A, 518, L47 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Elbaz, D., et al. 2010, A&A, 518, L29 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gonzalez, A. H., Clowe, D., Bradac, M., et al. 2009, ApJ, 691, 525 [NASA ADS] [CrossRef] [Google Scholar]
- Griffin, M. J., et al. 2010, A&A, 518, L3 [Google Scholar]
- Johansson, D., Horellou, C., Sommer, M. W., et al. 2010, A&A, 514, A77 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Kneib, J., van der Werf, P. P., Kraiberg Knudsen, K., et al. 2004, MNRAS, 349, 1211 [NASA ADS] [CrossRef] [Google Scholar]
- Knudsen, K. K., van der Werf, P. P., & Kneib, J. 2008, MNRAS, 384, 1611 [NASA ADS] [CrossRef] [Google Scholar]
- Le Floc'h, E., Papovich, C., Dole, H., et al. 2005, ApJ, 632, 169 [NASA ADS] [CrossRef] [Google Scholar]
- Ott, S. 2010, in Astronomical Data Analysis Software and Systems XIX, ed. Y. Mizumoto, K.-I. Morita, & M. Ohishi, ASP Conf. Ser., in press [Google Scholar]
- Papovich, C., Rudnick, G., Le Floc'h, E., et al. 2007, ApJ, 668, 45 [NASA ADS] [CrossRef] [Google Scholar]
- Pereira, M., et al. 2010, A&A, 518, L40 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Pérez-González, P. G., Rieke, G. H., Egami, E., et al. 2005, ApJ, 630, 82 [NASA ADS] [CrossRef] [Google Scholar]
- Pérez-González, P. G., et al. 2010, A&A, 518, L15 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Pilbratt, G. L., et al. 2010, A&A, 518, L1 [CrossRef] [EDP Sciences] [Google Scholar]
- Poglitsch, A., et al. 2010, A&A, 518, L2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rawle, T. D., et al. 2010, A&A, 518, L14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rex, M., Ade, P. A. R., Aretxaga, I., et al. 2009, ApJ, 703, 348 [NASA ADS] [CrossRef] [Google Scholar]
- Rex, M., et al. 2010, A&A, 518, L13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rieke, G. H., Alonso-Herrero, A., Weiner, B. J., et al. 2009, ApJ, 692, 556 [NASA ADS] [CrossRef] [Google Scholar]
- Rigby, J. R., Marcillac, D., Egami, E., et al. 2008, ApJ, 675, 262 [NASA ADS] [CrossRef] [Google Scholar]
- Smail, I., Ivison, R. J., & Blain, A. W. 1997, ApJ, 490, L5 [NASA ADS] [CrossRef] [Google Scholar]
- Smail, I., Ivison, R. J., Blain, A. W., & Kneib, J. 2002, MNRAS, 331, 495 [NASA ADS] [CrossRef] [Google Scholar]
- Smith, G. P., et al. 2010, A&A, 518, L18 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Swinbank, A. M., Smail, I., Longmore, S., et al. 2010, Nature, 464, 733 [Google Scholar]
- Wilson, G. W., Hughes, D. H., Aretxaga, I., et al. 2008, MNRAS, 390, 1061 [NASA ADS] [CrossRef] [Google Scholar]
- Zemcov, M., et al. 2010, A&A, 518, L16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
Online Material
Appendix A: Ancillary data for the Bullet cluster
Table A.1: The Bullet cluster ancillary data.
Footnotes
- ... Overview
- Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA. Data presented in this paper were analyzed using ``The Herschel interactive processing environment (HIPE)'', a joint development by the Herschel Science Ground Segment Consortium, consisting of ESA, the NASA Herschel Science Center, and the HIFI, PACS and SPIRE consortia.
- ...
- Appendix is only available in electronic form at http://www.aanda.org
All Tables
Table 1: The HLS Bullet cluster data.
Table A.1: The Bullet cluster ancillary data.
All Figures
![]() |
Figure 1:
Left - Multi-wavelength imaging data of the Bullet cluster as indicated in each panel (see Appendix A for
references). The contours overlaid on the Chandra and IMACS
images are the weak-lensing mass map from Clowe et al. (2006). The
field of view is |
Open with DEXTER | |
In the text |
![]() |
Figure 2:
Comparison between the total infrared luminosities measured
by fitting the Rieke et al. (2009) SED templates to the observed data
points (Measured
|
Open with DEXTER | |
In the text |
Copyright ESO 2010
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.