A&A 451, 417-429 (2006)
DOI: 10.1051/0004-6361:20054446
H. Dole1 - G. Lagache1 - J.-L. Puget1 - K. I. Caputi1 - N. Fernández-Conde1 - E. Le Floc'h2,3 - C. Papovich2 - P. G. Pérez-González2 - G. H. Rieke2 - M. Blaylock2
1 - Institut d'Astrophysique Spatiale (IAS), bât. 121, 91405 Orsay Cedex, France;
Université Paris-Sud 11 and CNRS (UMR 8617), France
2 -
Steward Observatory, University of Arizona, 933 N Cherry Ave,
Tucson, AZ, 85721, USA
3 -
Associated with Observatoire de Paris, GEPI, 92195 Meudon, France
Received 31 October 2005 / Accepted 18 February 2006
Abstract
Aims. We quantify the contributions of 24 m galaxies to the Far-Infrared (FIR) Background at 70 and 160
m. We provide new estimates of the Cosmic Infrared Background (CIB), and compare it with the Cosmic Optical Background (COB).
Methods. Using Spitzer data at 24, 70 and 160 m in three deep fields, we stacked more than 19000 MIPS 24
m sources with
Jy at 70 and 160
m, and measured the resulting FIR flux densities.
Results. This method allows a gain up to one order of magnitude in depth in the FIR. We find that the Mid-Infrared (MIR) 24 m selected sources contribute to more than 70% of the Cosmic Infrared Background (CIB) at 70 and 160
m. This is the first direct measurement of the contribution of MIR-selected galaxies to the FIR CIB. Galaxies contributing the most to the total CIB are thus
luminous infrared galaxies, which have intermediate stellar masses. We estimate that the CIB will be resolved at 0.9 mJy at 70 and 3 mJy at 160
m. By combining the extrapolation of the 24
m source counts below
Conclusions. The MIPS surveys have resolved more than three quarters of the MIR and FIR CIB. By carefully integrating the Extragalactic Background Light (EBL) SED, we also find that the CIB has the same brightness as the COB, around 24 nW m-2 sr-1. The EBL is produced on average by 115 infrared photons for one visible photon. Finally, the galaxy formation and evolution processes emitted a brightness equivalent to 5% of the primordial electromagnetic background (CMB).
Key words: cosmology: observations - cosmology: diffuse radiation - galaxies: evolution - galaxies: starburst - galaxies: infrared
The cryogenic infrared space missions IRAS (Infrared Astronomical
Satellite) and ISO (Infrared Space Observatory) provided us with
valuable insights to the IR-dominated galaxies in the Mid-Infrared
(MIR) and FIR (Sanders & Mirabel 1996; Genzel & Cesarsky 2000; Elbaz 2005; Lagache et al. 2005; Dole 2003, for
reviews). ISO
MIR surveys were able to resolve a significant fraction of the
15 m CIB (Elbaz et al. 1999, counts close to convergence). Using model
SEDs of galaxies (Chary & Elbaz 2001; Lagache et al. 2003; Xu et al. 2001, for instance),
the contribution of MIR-selected galaxies to the peak of the CIB
(around 140 to 170
m) can be inferred. Elbaz et al. (2002) derived
that
% (
over
nW m-2 sr-1)
of the 140
m background is due to ISOCAM 15
m galaxies,
whose median redshift is
.
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Figure 1:
Sensitivity to the bolometric luminosity (and star
formation rate, assuming star forming galaxies) of various infrared
and submillimeter experiments. Detections of at least 10 sources in
the surveys can be made in the areas above the curves. We assumed
the scenario of a typical deep survey. ISOCAM 15 ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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The Spitzer Observatory (Werner et al. 2004) is performing much
deeper and wider-area surveys, in particular at 24, 70 to 160 m
using the Multiband Imaging Photometer for Spitzer (MIPS)
(Rieke et al. 2004). However, because of the limited angular resolution
("smoothing'' the high spatial frequency signal in the FIR maps),
deep MIPS 70 and 160
m maps are confusion limited
(Dole et al. 2003,2004b) - the source surface density corresponds
to 20 beams per source or less e.g. in the GTO fields. The FIR images
do not allow us to directly probe the same galaxy population as that
detected at 24
m, where the extragalactic source confusion is
less important. Figure 1 shows the typical
sensitivity of MIPS surveys to the bolometric luminosity of galaxies
as a function of redshift, using the modeled starburst SED of
Lagache et al. (2004). At a redshift
,
MIPS FIR surveys are
sensitive to ultraluminous IR galaxies (ULIRGs,
)
where MIPS 24
m surveys can probe luminous IR
galaxies (LIRGs,
). It is therefore
impossible to derive MIR and FIR SEDs of individual LIRGs at
and above.
MIPS can detect high redshift sources at 24 m: about 25 to 30%
of the population of galaxies lie at
,
at faint flux
densities (down to few tens of
Jy)
(Le Floc'h et al. 2004; Lonsdale et al. 2004; Pérez-González et al. 2005; Caputi et al. 2006; Chary et al. 2004; Houck et al. 2005; Egami et al. 2004).
Papovich et al. (2004) showed that MIPS surveys resolve about 70% of the
24
m IR galaxy CIB for
Jy. In comparison, MIPS
70 and 160
m (Dole et al. 2004a) surveys detect only about 20%
and less than 10% of the CIB at 70 and 160
m, respectively.
Programs of very deep 70
m imaging on small fields
(e.g. D. Frayer, private communication) are likely to resolve a larger
fraction, but due to confusion noise the FIR CIB will still not be
significantly resolved into individual sources, while the MIR CIB at
24
m is well resolved.
In this paper, we use a stacking analysis method that takes advantage
of the good sensitivity of the MIPS 24 m MIR channel, to fill the
sensitivity gap between the MIR and the FIR surveys. By stacking the
FIR data at the locations of MIR sources, we statistically investigate
the FIR properties of 24
m-selected galaxies. In particular, we
quantify the contribution of the 24
m resolved galaxies to the 70
and 160
m background, put strong lower limits to the CIB, and
give new estimates of the 70 and 160
m background.
Throughout this paper, we adopt a cosmology with h=0.65,
and
.
The surface brightnesses (e.g. of
the CIB) are usually expressed in units of MJy/sr or nW m-2 sr-1. For a given frequency
in GHz and wavelength
in microns, the conversion between the two
is given by:
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(1) |
Papovich et al. (2004) showed that the 80% completeness level
at 24 m in the GTO deep fields is reached at
Jy.
Nevertheless, Papovich et al. (2004) and Chary et al. (2004) show that the
detection of very faint 24
m sources, down to
Jy, is possible, but with increased photometric uncertainties and
reduced completeness (to lower than 5% at the GTO depth and 20% at the GOODS
depth).
Dole et al. (2004a) showed that at 70 and 160 m sources can be
safely extracted down to 15 mJy and 50 mJy, respectively. The
Frayer et al. (2006) results go deeper. However, confusion limits the
extraction of sources fainter than typically 56
Jy at 24
m,
3.2 mJy at 70
m, and 36 mJy at 160
m (Dole et al. 2004b). A
priori information on the existence of a source deduced from shorter
wavelength and less confusion-limited observations can extend the
reliable detection threshold below this nominal confusion limit.
To implement this approach, we build a sample as follows:
At 24 m, the detector pixel size is 2.5 arcsec, the FWHM
of the point spread function (PSF) is 6 arcsec, and the plate scale of the mosaic is chosen to be 1.25 arcsec. At 70
m, the detector pixel size is 9.9 arcsec,
the FWHM of the PSF is 18 arcsec, and the plate scale of the mosaic is chosen
to be 4.5 arcsec. At 160
m the detector pixel size is 18 arcsec, the FWHM of the PSF is 40 arcsec, and the plate scale of the
mosaic is chosen to be 18 arcsec (Rieke et al. 2004; Gordon et al. 2005, for more
details). The 70 and 160
m mosaics have
been resampled to the scale of the 24
m mosaic (1.25 arcsec
per pixel) using a bilinear interpolation. This last step greatly
facilitates the weight management of the three maps, since each has
different coverage, and it allows easy extraction of the signal at the three
wavelengths for the same sky position.
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Figure 2:
Images at 24, 70 and 160 ![]() ![]() |
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For each S24 flux density bin we select every 24 m source,
extract a square image about 440 arcsec on a side centered on
the source, and store it. We proceed similarly on the
mosaics at 70 and 160
m, extracting images at the position of
each 24
m source regardless of the presence of a detected FIR
source. The products at this stage are thus three cubes of data at 24,
70 and 160
m with the same dimensions (same number of source images and
same box size) for each of the 24
m flux density bins.
We then add the images in each cube at each wavelength, to generate a
stacked image of sources at 24, 70 and 160 m for a given S24flux bin. This operation is a simple sum, without any outlier
rejection. When stacking, we rotate each image by
with
respect to the previous one (and so on), to cancel out the large-scale
background gradients such as the prominent zodiacal background at
24
m. This processing is done both in each field separately as
well as using all the data at once. Unless otherwise stated, we use
the stacked data of all the fields together in the rest of this paper.
We checked that no significant signal was detected when we added a
random or systematic artificial offset to each 24
m position and
then performed exactly the same sub-image extraction and stacking as
we did for the real 24
m source list. Figure 2
shows the results of stacking the sources (only from the brightest
bin), with a random position offset added prior to the sum. No source
appears in the center, as expected. This guarantees that the stacking
method does not introduce an artifact that mimics a source.
Since the stacking analysis aims at statistically detecting faint
unresolved sources at 70 and 160 m, in principle there is no need
to also stack data at 24
m, where all sources are
resolved. However, doing so allows us to double-check the method,
since we know by design what the stacked photometry should be.
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Figure 3:
Images at 24 ![]() ![]() ![]() ![]() ![]() |
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Figure 4:
Images at 70 ![]() ![]() |
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Figure 5:
Images at 160 ![]() ![]() |
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Figure 6:
Normalized radial profiles of the stacked images. The
crosses represent the data, and the solid line the empirical
PSF. The vertical dotted lines show the radii of the aperture used
for photometry. From top to bottom: faintest S24 bin at
70 ![]() ![]() ![]() ![]() |
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Figure 7:
Top: confidence Level of the detections at 70 (dash) and
160 ![]() |
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The final stacked images at 24, 70 and 160 m as a function of the
24
m flux density S24 are presented in
Figs. 3-5, respectively. We report also in these figures the
number of sources stacked in each of the S24 bins. The figures
show clear detections of stacked sources at 70 and 160
m for
every S24 bin, even the faintest corresponding to
Jy. Given the surface density of the 24
m
sources at 60
Jy of
sr-1(Papovich et al. 2004), this translates to 1.04 and 0.2 beams per
source at respectively 70 and 160
m (Dole et al. 2003, using beams from their
Table 1). This is well beyond the confusion limits at these
FIR wavelengths (Dole et al. 2004b). This statistical detection of FIR
sources already demonstrates the great potential of this technique to
probe FIR galaxies down to levels below the confusion, thanks to
the excellent quality of the pointing and the stability of the
effective PSF (see below).
We check that the radial profile of the stacked sources is in
agreement with the PSF profile, at each wavelength and for each flux
bin. We show in Fig. 6 two profiles at each
wavelength corresponding to the extreme cases: the brightest and
faintest S24 flux bins. We used both the empirical PSF (from
bright sources) and the modeled STinyTim MIPS PSF
(Rieke et al. 2004; Gordon et al. 2005; Krist 1993). At large S24, the stacked
radial profiles at 70 and 160 m (bottom plots in
Fig. 6) agree well with the PSF in the
central part. At the faintest fluxes (top plots), the agreement is
good down to about 10% of the peak brightness. Since the stacked
images visually represent the 2-dimensional correlation function of
galaxies, the potential presence of many neighboring sources at small
scales (source clustering) might have widened the radial profile,
which is not observed; thus source clustering does not contribute
significantly to the noise budget.
We measure the flux density of the stacked sources with aperture
photometry and correct for aperture size. The radii of the
apertures and reference annulus are, in arcseconds: (
,
,
) = (12.2, 17, 24), (30, 49, 79) and (54, 90, 126)
for 24, 70 and 160
m, respectively. These radii correspond to
approximatively 3, 5 and 7 times the FWHM in the FIR and 2, 3, 4 times
the FWHM in the MIR. We measured the noise in each image by using
about 2000 measurements on random positions. We compute the confidence
level (C.L.) of each detection (top of Fig. 7) using
the cumulative distribution of the noise measurements. The deviation from
100% of the C.L. is the probability that the noise creates a spurious
source. For the faintest bin, the C.L. is around 80%, and it rises to
97% for the next four bins, and stays at 100% for the brighter
S24 bins. We fitted a Gaussian function to the distribution of
noise to get the standard
deviation in order to estimate the S/N ratio. This method works for the brighter bins (middle panel in
Fig. 7), where the flux distribution is indeed nearly
a Gaussian distribution. In this range, the S/N values have a median of 8 at
70
m and 7 at 160
m. In the three faintest bins, the
noise distribution is not Gaussian, because of the presence of
slightly brighter sources; the Gaussian fit is therefore not relevant and
we opt for the C.L. technique. The bottom plot in Fig. 7 shows the average FIR
flux per stacked galaxy. A set of
100
Jy MIR-selected
galaxies would have a typical average FIR flux of
0.5 and
3 mJy if taken individually at 70 and 160
m, respectively. Since
the confusion limits are at about 3 and 40 mJy at these wavelengths
(Dole et al. 2004b), the gain of the stacking analysis technique is one
order of magnitude in flux compared to individual detection.
Finally, it is not necessary to remove the brightest sources for the goals of this paper,
because we stack typically 1000 to 2000 galaxies per flux bin, so their
influence is negligible except maybe in the 3 faintest bins.
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Figure 8:
Contributions to the CIB: brightness of stacked sources at
160 and 70 ![]() ![]() ![]() |
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The brightness of the stacked sources at 70 and 160 per logarithmic
flux density bin, or
,
as a function of
the 24
m flux bin, is presented in
Fig. 8.
in MJy/sr is defined as the
total stacked flux density divided by the survey area.
Using a logarithmic flux density bin allows
direct comparison of the contribution in energy of each bin to the
CIB, and is directly related to the differential source counts with a
scaling factor
.
In the range
Jy, both contributions to the CIB present a maximum, which
shows that the contributions have reached convergence.
Converting S70 and S160 into
S24 using the color ratios of 9 and 30 (see
Table 2 below), this means the FIR CIB will be mainly
resolved at
mJy and at
mJy. We have also plotted the source counts of
Dole et al. (2004a) and Frayer et al. (2006); we used the conversion to
S24 as given by color ratios relevant for bright galaxies of 20
and 60 at 70 and 160
m, measured on the very bright
end of the bottom plot in Fig. 7. Despite this
simplifying assumption of a single color ratio, there is excellent
agreement between the brightness derived from the stacking analysis
and the source counts. This plot can be used to constrain models of
galaxy evolution.
Sample variance plays a role in these results. To probe its effects,
we split each of our three fields (CDFS, HDFN, LH) into four subfields
of about 250 square arcmin each, and performed an independent analysis
on each of these twelve subfields. We obtain contributions varying in
some cases by as much as a factor of two (peak-to-peak). For
instance, computing the standard deviation of the distribution of the
cumulative 160 m flux (the faintest points in
Fig. 10) measured over these 12 subfields gives
MJy/sr and a mean and median both of 0.53 MJy/sr. Renormalizing by the twelve sub-fields gives
:
the uncertainty induced by the Large Scale Structure variations across
the fields is of order 15%.
From here on in this paper, our error budget takes into account: 1) the calibration uncertainties; 2) the photometric uncertainty; 3) the large-scale structure (sample variance).
To compute the fraction of background resolved with the stacking
analysis of the MIPS data, we first need to review the measurements of
the total CIB, in particular at 24, 70 and 160 m. It should be
remembered that the total cosmic background contains the contribution
of all extragalactic sources but also more diffuse emissions,
e.g. from dust in galaxy clusters (Montier & Giard 2005). Furthermore
the extragalactic sources are expected to be mostly galaxies but it
cannot be excluded that other lower luminosity sources, population III
stars for instance, contribute significantly but will not be detected
directly in the present deep surveys.
Measuring the CIB directly by photometry is particularly difficult
because one needs 1) an absolute photometer and 2) a proper estimate
of the foreground. The two FIR channels of MIPS are not absolute
photometers for the very extended spatial scales, since no internal
calibrated reference can be observed to calibrate absolutely the slow
response. A better knowledge of the instrument in the future may allow
a proper absolute calibration, using its "Total Power'' mode,
similarly to what has been done successfully in the past, e.g. with
ISOPHOT at 170 m on some selected low surface brightness fields
(Lagache & Dole 2001). However, MIPS is by design well calibrated for
small spatial scales, e.g., point sources, because the frequent
stimulator flashes and the scanning strategy (acting like a chopping
mode) properly track the fast response of the photoconductors
(Gordon et al. 2005,2006, for instance). For these reasons,
we do not use MIPS as an absolute photometer to estimate the level of
the CIB and the foregrounds, but as a detector of small scale
fluctuations to resolve the CIB based on 24
m source
observations. Our approach has the important advantage that it is not
biased by the foregrounds and their modeling, which can lead to
significant errors.
We therefore start by reviewing the direct measurements, using absolute
photometry in large beams, provided mainly by the COBE FIRAS and DIRBE
experiments and also the IRTS and rocket experiments in the near
infrared (m). These measurements can be combined with indirect upper
limits derived from observations of gamma rays from distant Blazars at
TeV energies.
To use the FIRAS and DIRBE data to provide CIB absolute measurements
requires an accurate component separation. Local
extended emission from interplanetary and interstellar dust can be
removed using their specific SEDs and anisotropic spatial
distributions traced independently, as well as time variability for the
zodiacal emission and scattering (Hauser & Dwek 2001, for instance).
Early gamma ray data from Blazars from the CAT experiment led to
upper limits on the CIB intensity significantly lower than the DIRBE
residuals as pointed out by Renault et al. (2001) and
Wright (2004). Recent results on more distant Blazars
(Aharonian et al. 2005; Schroedter 2005) constrain the
CIB even more in the near and thermal infrared. Together with lower limits
obtained by integrating the galaxy counts from HST, ISO, and Spitzer, these measurements tightly constrain the Extragalactic
Background Light between 0.8 to
m.
At 160 m, the CIB can be interpolated from the DIRBE/COBE
measurements at 100
m (Lagache et al. 2000) and 140 and 240
m
(Hauser et al. 1998):
,
,
MJy/sr, respectively. If the FIRAS photometric scale is used in the
calibration (rather than the DIRBE photometric calibration), lower
values are obtained at 140 and 240
m: 0.7 MJy/sr and 1.02 MJy/sr
(Hauser et al. 1998). A large uncertainty in the determinations at 100
and 140
m comes from the zodiacal emission removal, as is also
true at 60
m. The DIRBE zodiacal emission model was obtained by
Kelsall et al. (1998) relying on the variability with viewing geometry.
Its accuracy can be estimated a posteriori using the residuals
observed at wavelengths where the zodiacal emission is at a maximum (12
and 25
m). The residual emission, obtained by Hauser et al. (1998),
has in fact a spectrum very similar to the zodiacal one. The
residuals are about
Wm-2 sr-1 at 12 and
25
m, far above the upper limit derived by high-energy
experiments like HESS (Aharonian et al. 2005), but not very much
larger than the uncertainties of the Kelsall et al. (1998) zodiacal
emission model. A conservative estimate of the amount of zodiacal
emission not removed in this model at 12 and 25
m is therefore about
Wm-2 sr-1. Using the Kelsall et al. (1998)
smooth high latitude zodiacal cloud colors, the amount not removed at
100, 140 and 240
m translates to 0.30, 0.14, 0.045 MJy/sr,
respectively. This reduces the CIB from 0.78 to 0.48 MJy/sr at
100
m, from 1.17 to 1.03 at 140
m and from 1.09 to 1.05 at
240
m. Adopting the FIRAS photometric scale gives at 140 and
240
m, 0.56 and 0.98 MJy/sr respectively. From the above
discussion, we see that the CIB at 140
m - the closest in
wavelength to the 160
m MIPS bandpass - is still uncertain
by a factor of about 2 because of the uncertainty in the zodiacal
level. The DIRBE/FIRAS measurement of the CIB at 240
m suffers
less from zodiacal residuals and photometric calibration uncertainty.
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Figure 9:
Current measurements of the Extragalactic Background
Light Spectral Energy Distribution from 0.1 ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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A firm upper limit of 0.3 MJy/sr at 60 m has been derived by
Dwek & Krennrich (2005) using observations of TeV gamma ray emission from
distant AGNs. Miville-Deschênes et al. (2002) uses a fluctuation analysis
of IRAS maps to set an upper limit of 0.27 MJy/sr and give an estimate
of 0.18 MJy/sr, on the assumption that the level of
fluctuations-to-total intensity ratio is not strongly wavelength
dependent.
At 24 m we use for the contribution of IR galaxies to the CIB
the estimate of Papovich et al. (2004) of
2.7+1.1-0.7 nW m-2 sr-1. This value comes from 1) integration of the
source counts down to 60
Jy giving
nW m-2 sr-1; 2) extrapolation of the source counts to
lower fluxes, giving a contribution of
0.8+0.9-0.4 nW m-2 sr-1; and 3) upper limits from Stecker & De Jager (1997) and
from CAT (Renault et al. 2001).
The most constraining measurements and lower and upper limits on the
Cosmic Optical Background (COB) and the CIB from 0.1 m to 1 mm
are all reported in Fig. 9. The Lagache et al. (2004)
model predicts a CIB at 240
m of 0.98 MJy/sr, which is in very
good agreement with the estimate from combined measurements discussed
above. Furthermore this model agrees with the observational
constraints (e.g. number counts, CIB intensity and fluctuations). We can
thus take the CIB values from this model as a reasonable interpolation
between the better constrained CIB values at shorter and longer
wavelengths: 0.82 MJy/sr at 160
m, and 0.15 MJy/sr at 70
m.
To estimate the contribution of MIR sources to the background, we
add up the brightnesses of all the S24 bins to get the integrated
light at 24, 70 and 160 of all the resolved 24 m sources. Each
S24 bin is corrected for incompleteness. The results are
presented Table 1, and Fig. 10 shows
the cumulative integrated light from galaxies in the FIR as a function
of S24. For a sanity check, we obtain that at 24 microns the percentage of
the CIB that is resolved is 79%, which is in agreement with
Papovich et al. (2004) within the error bars. At 70 and 160 micron we
resolve 92% and 69% of the background, respectively.
Half of the 24 m CIB is resolved by sources with
Jy. In the FIR, half of the 70
m CIB is resolved by 24
m
sources brighter than
Jy, and half of the
160
m CIB is resolved by 24
m sources brighter than
Jy. This difference between 70 and 160
suggests that the CIB at 160
m is dominated by galaxies at
slightly higher redshift than at 70
m, a consequence of the
spectral shape of LIRGs and ULIRGs or, equivalently, the effect of
k-correction. This point is illustrated in Figs. 5 and 6 of
the review by Lagache et al. (2005).
To put in perspective the problem of resolving the CIB and what the
stacking analysis accomplishes, we plot in
Fig. 11 the new observed constraints on the
extragalactic background SED. The fraction of the CIB resolved at
MIPS wavelengths by unbiased surveys was 79%, 20% and 7% at
respectively 24, 70 and 160 m (Papovich et al. 2004; Dole et al. 2004a).
When using the present stacking analysis, this fraction rises to 92%
and 69% at 70 and 160
m respectively, and is represented by the
red lower limits (see also Table 1).
Based purely on observations without modeling of galaxy SEDs, we find that most of the FIR background is resolved into MIR galaxies. This confirms the model-dependent result of Elbaz et al. (2002). This analysis is the first direct resolution of the CIB simultaneously in the MIR and the FIR.
Table 1:
Contribution to the CIB of
Jy
galaxies. Sources of uncertainty come from photometry, calibration,
and large scale structure. The CIB column gives the best estimate
from the discussion in Sect. 4.1.
Table 2:
Mean observed colors in
of
Jy galaxies contributing to the CIB.
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Figure 10:
Cumulative brightness ( left axis, in MJy/sr) and fraction
of the background resolved ( right axis) at 160, 70 and 24 ![]() ![]() ![]() |
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Looking at the 24 m number counts of Papovich et al. (2004), one can
see that the bulk of 24
m CIB is mainly due to sources with
Jy. We select three cuts in S24 to
investigate the colors of the contributions to the CIB by different
galaxy populations. In the following, redshifts come from
Caputi et al. (2006) (see their Fig. 5), and the relative
contributions come from the integration of the Papovich et al. (2004)
source counts and the Lagache et al. (2004) model. The cuts are:
These colors can be interpreted as the SED of a LIRG being redshifted,
since fainter 24 m sources lie at larger redshifts: the 160/70
ratio increases (with decreasing flux) because the peak of the big grains'
FIR spectrum
is shifted longwards of 160
m. The color ratios involving the
24
m band are less obvious to interpret, since the Polycyclic
Aromatic Hydrocarbon (PAH) (Puget & Leger 1989) features (especially
between 6.2 and 8.6
m) and the silicate absorption feature are
redshifted into and then out of this band. The 70/24 ratio evolution
might have for its origin a mix of PAH (increasing the 24) and
very small grains continuum (decreasing the 70) being redshifted, that
cancel out each other.
If one wants to extrapolate the contribution of fainter (
Jy) MIR galaxies to the FIR CIB, a conservative approach is to
use a constant 160/24 and 70/24 color ratio for the unresolved
population. To set these ratios, we take the colors from the
faintest population (
Jy); this faint
population presumably has the closest characteristics to the
unresolved one. We will therefore use
,
and
(from Table 2). Since
the contribution to the CIB of these faint galaxies is modest
(30% at most), the large uncertainties in these color ratios will
not dominate the total background estimate.
The present stacking analysis performed on detected galaxies
Jy gives strong measured lower limits to the CIB
due to galaxies at 70 and 160
m, without requiring any
modeling. To determine upper limits to the FIR CIB requires
a different approach. There are many difficulties at 70
m in
extracting an accurate value of the CIB, mostly due to the
problems in the removal of the zodiacal component
(Renault et al. 2001; Finkbeiner et al. 2000, for instance). At 160
m the CIB
estimate is more robust, but still with a significant uncertainty
(factor of
3, see Sect. 4.1).
Another way to get a good estimate of the FIR galaxy CIB brightness is to
estimate the unresolved 24 m background fraction, use the 160/24
and 70/24 colors measured for the weakest sources, and then apply
these colors to the unresolved part to get the 70 and 160
m
background estimates. Thus, we extrapolate
the colors of galaxies with
Jy using the
colors of the
Jy galaxies
derived in the previous section. To estimate
the unresolved 24
m background, Papovich et al. (2004) used a simple
extrapolation of the differential number counts. Since the slope of
the counts below 100
Jy is strongly decreasing (
in
), the integral is dominated by the largest fluxes
S24. The estimate is robust, unless a hypothetical faint
population exists. The remaining unresolved 24
m background
created by
Jy sources is therefore 0.54
,
(to be compared to 2.16
for
Jy sources).
![]() |
Figure 11:
Extragalactic background light spectral energy
distribution from 0.1 ![]() ![]() ![]() ![]() ![]() ![]() |
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We derive the extrapolated FIR CIB level due to IR galaxies using:
![]() |
(2) |
Our estimate at 70 m is higher than the Lagache et al. (2004) model
estimate by 11%, and lower by about 13% at 160
m.
About 25% of the CIB brightness at 70 and 160
m comes from faint
MIR sources (
Jy). Assuming our new FIR CIB values
represent the actual CIB values, we estimate that our stacking
analysis of
Jy galaxies finally resolves 80%
of the background at 70 and 160
m. We also show that the
population dominating the CIB is made of galaxies seen at 24
m
and their simplest extrapolation to lower fluxes.
In the near and mid-IR, upper and lower limits tightly constrain the
EBL SED: 1) with HST+Spitzer and HESS between 0.8 and
4 m, and 2) with ISO, Spitzer and CAT between 5 and
24
m. In this range, the EBL SED is constrained to better than
50% (and to the 20% level in several wavelength ranges). The EBL is
now also well constrained in the FIR; direct measurements of the
diffuse emission and our new lower limits constrain the CIB SED to the
50% level.
The permitted zone for the EBL SED is presented in Fig. 12. This zone is defined as the area between current upper and lower limits. In this zone, the COB brightness ranges from 19.5 to 35.5 nW m-2 sr-1, and the CIB from 24 to 27.5 nW m-2 sr-1. The ratio COB/CIB thus ranges from 0.7 to 1.5.
Table 3:
Contributions of the 24m galaxies to the FIR CIB
in nW m-2 sr-1. For the
Jy galaxies,
a simple color extrapolation has been used, as described in
Sect. 5.
From these constraints, we may derive a conservative estimate of the
EBL SED, that typically lies between the upper and lower limits and
that makes use of well known physical processes. The CIB estimate,
based on the Lagache et al. (2004) model, agrees with the data and is
strongly constrained in the MIR and the 240-400 m range. It
strongly decreases with increasing frequency below 8
m because of
the main PAH features at 6.2 to 8.6
m being redshifted. The COB
estimate also decreases with increasing wavelength above 2
m
because of the old stellar population SED. This simple SED behavior is
in agreement with the model of Primack et al. (1999). Our reasonable guess
is that the COB and CIB have equal contributions around 8
m.
![]() |
Figure 12: Cosmic Optical Background and Cosmic Infrared Background due to galaxies permitted zone estimate (shaded area), using upper and lower values. See Fig. 9 for the other symbols. |
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Figure 13 shows our smooth EBL SED estimate (thick
line), as well as our best estimate of the COB (blue shaded) and the
CIB (red shaded). The overlap region where both COB and CIB contribute
significantly and the resulting total EBL is shown as the gray-shaded
area around 8 m. We find that the brightness of the COB is 23 nW m-2 sr-1, and 24 nW m-2 sr-1 for the CIB. The
ratio between the COB and CIB is thus of the order of unity for this
EBL SED.
Our results are in contradiction with Wright (2004) who finds a
COB/CIB ratio of 1.7, and values at least 50% higher than ours: 59 nW m-2 sr-1 (COB) and 34 nW m-2 sr-1 (CIB). However,
the Wright (2004) estimate came before the strong upper limits of
HESS (Aharonian et al. 2005) below 4 m. This limit puts the COB
much closer to the integrated light from galaxy counts than to the
diffuse measurements. From the galaxy counts and stacking analysis
(lower limits), and high-energy experiments (upper limits), the EBL is
now very well constrained. In particular, we can now securely state
that the contributions to the EBL of faint diffuse emissions outside
identified galaxy populations - too weak to be detected in current
surveys, like population III stars relic emission, galaxy clusters,
hypothetical faint IR galaxy populations - can represent only a small
fraction of the integrated energy output in the universe.
![]() |
Figure 13: Our best Cosmic Optical Background (blue-shaded, left) and Cosmic Infrared Background (red-shaded, right) estimates. The gray-shaded area represents the region of overlap. See Fig. 9 for the other symbols. |
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![]() |
Figure 14: Schematic Spectral Energy Distributions of the most important (by intensity) backgrounds in the universe, and their approximate brightness in nW m-2 sr-1 written in the boxes. From right to left: the Cosmic Microwave Background (CMB), the Cosmic Infrared Background (CIB) and the Cosmic Optical Background (COB). |
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It is interesting to update the contributions of the most
intensive electromagnetic backgrounds in the universe, as has been
done for instance by Scott (2000) or Wright (2004), and we
schematically represent these in Fig. 14. Obviously,
the Cosmic Microwave Background (CMB) dominates the universe's SED,
and accounts for about 960 nW m-2 sr-1. We showed that the
CIB and COB each account for 23 and 24 nW m-2 sr-1,
respectively. With a total of 47 nW m-2 sr-1 in the optical
and the Far-Infrared, the EBL represents about 5% of the brightness
of the CMB. Taking into account the complete SED of the EBL will not
change this picture, since the contributions to the total EBL
brightness of the radio, UV, X-ray (Hasinger et al. 2001; Mushotzky et al. 2000) and
ray (Strong et al. 2004) extragalactic
backgrounds are smaller by one to three orders of magnitude than the
COB and CIB (Scott 2000).
The galaxy formation and evolution processes provide 5% in
brightness of the electromagnetic content of the Universe. Half of
the energy comes in the form of starlight (COB) and half as
dust-reprocessed starlight (CIB). The maximum of the power
distribution is at
m for the COB and
m for
the CIB (Fig. 14). There are therefore on average 115
infrared photons for 1 visible photon emitted in these processes.
Our key points and results for the resolution and characterization of the FIR CIB and the EBL are:
Acknowledgements
This work is based on observations made with the Spitzer Observatory, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under NASA contract 1407. We thank the funding from the MIPS project, which is supported by NASA through the Jet Propulsion Laboratory, subcontract #1255094. This work also benefited from funding from the CNES (Centre National d'Etudes Spatiales) and the PNC (Programme National de Cosmologie). We thank Jim Cadien for the great help in the data processing. We thank Nabila Aghanim, Hervé Aussel, Noel Coron, Daniel Eisenstein, David Elbaz, Charles Engelbracht, Dave Frayer, Karl Gordon, Nicolas Ponthieu, Martin Schroedter, and Xianzhong Zheng for fruitful discussions.