A&A 410, 75-82 (2003)
DOI: 10.1051/0004-6361:20031201
L. Pentericci1 - H.-W. Rix1 - F. Prada2 - X. Fan3 - M. A. Strauss4 - D. P. Schneider5 - E. K. Grebel1 - D. Harbeck1 - J. Brinkmann6 - V. K. Narayanan4
1 - Max-Planck-Institut fur Astronomie, Konigstuhl 17,
69117, Heidelberg, Germany
2 - Instituto de Astrofisica de Canarias, 38205 La Laguna, Tenerife, Spain
3 - Steward Observatory, The University of Arizona
933 N. Cherry Ave, Tucson, AZ 85721-0065 Arizona, USA
4 - Princeton University Observatory, Princeton
08544, USA
5 - Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802, USA
6 - Apache Point Observatory PO Box 59,
Sunspot, NM 88349-0059, USA
Received 22 January 2003 / Accepted 4 July 2003
Abstract
We present J-H-K' photometry for a sample of 45 high redshift
quasars found by the Sloan Digital Sky Survey.
The sample was originally selected on the basis of optical
colors and spans a redshift range from 3.6 to 5.03. Our photometry reflects the rest-frame SED longward of Ly
for all redshifts.
The results show that the near-IR colors
of high redshift quasars are quite uniform.
We have modelled the continuum shape of the quasars (from just
beyond Ly
to
4000 Å) with a power law of the form
,
and find
with a scatter of 0.33. This value is similar to what is
found for lower redshift quasars over the same restframe
wavelength range, and we conclude that there is hardly any
evolution in the continuum properties of optically selected
quasars up to redshift 5. The spectral indices found by combining
near-IR with optical photometry are in general consistent but
slightly flatter than what is found for the same quasars using
the optical spectra and photometry alone, showing that the
continuum region used to determine the spectral indices can
somewhat influence the results.
Key words: galaxies: active - quasars: general - infrared: general - cosmology: observations
In this paper we aim
to determine the continuum properties of high redshift quasars at optical restframe wavelengths.
To do this we have obtained
J-H-K' photometry of a large color-selected sample
of high redshift quasars found by SDSS.
A good knowledge of the quasar continuum shape at near-UV/optical restframe
wavelengths is important for several reasons.
Over the near-UV/optical wavelength range
the shape of the continuum is usually approximated with a single
power law of the form
.
The mean value of
,
the dispersion of this value, and even the validity of the
power law parameterization as well as the evolution
of such parameters with redshift are still under debate (e.g. Vanden Berk et al. 2001 and references therein).
The continuum slopes of quasars are blue,
with a mean canonical spectral index of
(e.g. Richstone & Schmidt 1980),
but several results of the past few years point to flatter continua
(e.g. Francis 1996;
Natali et al. 1998; Vanden Berk et al. 2001),
and indicate a different slope
at different restframe wavelength ranges.
On the other hand the most recent results of Fan et al. (2001a) and Schneider et al. (2001), who find
steeper average indices (respectively
and -0.9)
for very high redshift quasars, seem to point to an evolution of the continuum properties of quasars with redshift.
However, as discussed in Schneider et al. (2001),for high redshift quasars,
determination of the continuum slope from optical data alone (
)
must rely on a small restframe wavelength region with
Å.
For example in objects
at
,
the restframe V-band emission is shifted to K-band. Therefore near-IR
data are essential to unambiguously determine the continuum properties of high redshift quasars in a way comparable to low-redshift objects, so as to get an unbiased measure of evolution.
A knowledge of the optical continuum shape and its possible redshift evolution,
is not only important to understand the quasars itself but
also for selecting objects at even higher
redshifts. Optical colors alone begin to be less efficient for selection purposes at ,
since the quasars
evolutionary track crosses the locus of very
low-mass, late-type stars.
Already, the highest redshift quasars discovered to date have been selected by adding J-band photometry
to the SDSS colors,
to distinguish quasar candidates from stars
(see in particular Zheng et al. 2000 and Fan et al. 2001a).
In addition, determining
the flux decrement in the Ly
forest needs an
estimate of the continuum at
,
which is usually an extrapolation from
m.
If this is done by using the classical
index
it can lead to uncertainties of 5-10% in the
computation of the continuum decrement.
Also for high redshift quasars the observed optical fluxes must be extrapolated to obtain the optical luminosity MB, e.g. to determine the luminosity function. Any change of
with redshift could substantially influence the inferred luminosity. Only with near-IR photometry can
MB be determined directly. Lastly, for the SDSS quasar search,
a knowledge of the continuum slope is essential for
modeling the SDSS quasar selection function which is then used to derive the luminosity function (Fan et al. 2001b).
1. gri candidates, selected principally from the
g*-r*, r*-i* diagram:
![]() |
(1) |
2. riz candidates, selected principally from the
r*-i*, i*-z* diagram:
![]() |
(2) |
Within these color magnitude boundaries, two subsamples were selected for observations in Spring and Fall. The first is the color selected sample in the Fall Equatorial Stripe, presented in Fan et al. (2001a), which comprises 39 objects. The second is a complete sample in the Spring Equatorial Stripe, consisting of 55 objects whose redshifts have been reported in different papers (Fan et al. 2000; Schneider et al. 2001; Anderson et al. 2001; Fan et al. 2003). Since the two samples have been selected with the same optical color criteria they can be merged together and form a large color selected sample, spanning a redshift range from 3.60 to 5.03.
The completeness of the Fall sample has been extensively discussed in Fan et al. (2001a) and is around 80%, depending slightly on redshift; the completeness for the Spring sample should be very similar. As we detail below, we have observed a random subsample of 45 of the 94 quasars. Therefore our sample can be viewed as a statistical sample with the above color cuts.
Table 1: Observations log.
Each target was observed through the J, H, and K' filters. The K' band (Wainscoat & Cowie 1992) was preferred to the K band to reduce the effects of thermal emission from the sky and the telescope. Each object was observed for a total on-target exposure time between 10 and 12 min in each filter. For a satisfactory background subtraction, the images were dithered on a 6 position pattern (4 positions for the first run), with offsets of around 30'' between each frame. We took 6, 12 or 18 frames per object depending on the night and on the brightness of the object. At each position the total integration time was split into short sub-frames to avoid saturation (the frames were directly integrated at the telescope). In Table 1 we report all these observational parameters, namely the total integration time, the sub-integration times and the number of frames at each position.
During each night, 4 or more different standard stars (UKIRT faint stars from Elias et al. 1982, complemented by those observed in the same fields by Hunt et al. 1998) spanning a range of colors were observed in each of the filters at regular intervals (at least 3 times per night). In most cases the standards span the same range of airmasses as the targets. From the fall sample a total of 29 objects (out of 39) were observed under photometric or nearly photometric conditions. From the spring sample a total of 16 (out of 55) objects were observed. The selection of the objects was only determined by chance and observability so it is unbiased with respect to quasar properties. Therefore a total of 45 objects form a statistically well defined sample with complete near-IR photometry.
Note that the J, H and K' data for a given object were taken on a single night, while
the near-IR data were obtained one to two years after
the optical fluxes were measured from SDSS, so we cannot exclude the possibility that variability
could influence some of the results,
such as the determination of the spectral indices of the continuum slopes.
For example, a variability of 10-20% in the optical
flux could change the measured slope by 0.2.
Data reduction was performed with IRAF.
The sky-background was subtracted using a composite
sky frame made for each image from the previous and following images.
Typically five neighboring frames were used to create a sky image,
although in a few cases when the sky was
changing more rapidly we used only three frames.
Dome flats were obtained by
taking exposures with dome lamps on and off and subtracting one from the other; these were applied after sky subtraction (an alternative flat field was also created by averaging a large number of sky-frames,
masking out the brightest stars).
The background subtracted, flatfielded images were
shifted to a common reference, with shifts derived
from centering the position of as many point sources
as were visible in the frames.
In most cases at least four or more such reference stars were present,
but in a few objects only one reference could be used.
The registered images were then co-added using the IRAF/avsigclip
rejection algorithm.
With the large number of frames for each target (typically 12),
it was easy to perform cosmic ray rejection.
Photometric calibration was done using at
least five standard stars to derive the zero point of the three
bands. During each good night the scatter in the photometric zero point
was less than 0.05 (slightly higher for J band), without color correction so
all the standard stars in a given
band were simply averaged to give the final calibration.
The photometry is accurate to 0.1 magnitudes for the bright
part of the sample.
Magnitudes were derived inside circular apertures with radius of 4''.
The K' filter, as opposed to the standard K filter, does not
have many published values for standard star photometry,
but for some stars
interpolated K' magnitudes were available
from the web page developed by Dave Thompson.
For those stars which did not have K' magnitudes
available we simply used the K band magnitude
from Hunt et al. (1998).
![]() |
Figure 1: The J,H and K' magnitude of the quasars plotted as a function of redshift, with photometric uncertainties indicated by the errorbars. |
Open with DEXTER |
![]() |
Figure 2:
The near-IR colors of the sample quasars plotted as a function of redshift.
The dashed lines are the color expected from an object with a
power law continuum of slope
![]() ![]() |
Open with DEXTER |
![]() |
Figure 3: The spectral energy distribution of all quasars: all near-IR magnitudes have been transformed into the AB system (see text for details). The observed values have been shifted to the restframe of each object and normalized to have the same i-band magnitude. The lines indicate power laws with spectral indices from -0.25 to -1.0 (from the lower to the upper line). The object with colors much brighter than the other is 2256+0047, one of those whose continuum is not well represented by a power-law. It could be also a variable quasar. |
Open with DEXTER |
In Fig. 2 we have also plotted as dashed lines
the colors expected for a quasar if the continuum were
a perfect power law with a spectral index
and
respectively. From the continuum only,
the colors expected would be
z-J=1.08, J-H=0.69 and J-K'=1.22 for
.
The solid lines in each panel represent the colors
produced by shifting the composite SDSS quasar spectrum
by Vanden Berk et al. (2001) to the different redshifts.
This spectrum is best represented by a slightly
flatter power law continuum (
)
and of course contains the contribution
of all emission lines and features.
The two lines deviate substantially from each other only in the z-J color
for objects at redshift >4.5, due to the contribution of CIV entering
the z-band, and in the J-H color for redshift less than
4,
due to the
contribution of the MgII and the FeII complex in J band (Richards et al. 2001; Barkhouse & Hall 2001).
From the plots it is clear that the individual quasars show scatter in their colors around the predicted mean color lines. The scatter is far in excess of the measurement errors. Such scatter is produced by several factors, including the intrinsic differences of the spectral properties of quasars, which can have bluer or redder continua and the different relative strength of the emission lines in different objects. Note that in Fig. 2, the object at z=4.92 with colors deviating substantially from the expected ones, is a BAL quasar SDSSJ 160501.21-011220.6 (Fan et al. 2000), which shows quite unusual optical colors (see discussion in Hall et al. 2002). Apart from this object and SDSS J103432.72-002702.6, which is a mini BAL, there are no other BAL quasars in the sample.
There are only few near-IR measurements available in the literature for quasars at a similar redshift (e.g. Rodriguez Espinosa et al. 1988; Bechtold et al. 1994; Francis 1996; Zheng et al. 2000), all indicating colors similar to what we find.
Note that Zheng et al. (2000) used z-J< 1.5 and J-K<1.8 as additional constraints to select candidate high redshift quasars, whereas Fan et al. (2001b) used only z-J< 1.5.
Table 2: Near-IR multiband photometry of high redshift SDSS quasars.
We see that actually all except 3 of the objects satisfy the first constraint, and only one does not satisfy the second criterion. Indeed all L and M dwarfs stars found by combined SDSS plus 2MASS photometry have z-K > 2 (Finlator et al. 2000; Leggett et al. 2002) so their colors are quite different from those of quasars. These results confirm that the addition of one single near-IR band information to the SDSS photometry can greatly improve the efficiency of finding high redshift quasars. ![]() |
Figure 4:
Left: the distribution of the quasars continuum power-law index ![]() ![]() |
Open with DEXTER |
For a large fraction of the objects in the sample
the strength of the CIV line is known, having been measured from the
low resolution discovery spectra (Fan et al. 1999,2001a,2003 in preparation; Anderson et al. 2001; Schneider et al. 2001).
The strength of the other lines was not known so we used the average
equivalent width derived from the combined spectra of
SDSS quasars by Vanden Berk et al. (2001).
In particular we used EW=23.78 Å for CIV (when the real
value was not available),
EW=21.19 Å for CIII], EW= 34.95 Å for MgII and EW=46.21 Å for H(these are all restframe values).
Note that in most cases the
contribution of line emission flux to the broad band flux is less than 0.1 mag,
so it is comparable to or less than the photometric error.
We subtracted the line contribution from the relevant broad band values
and then converted magnitudes into flux.
The corrected continuum fluxes were then modeled with a
power law of the form
and the best fitting
spectral index
was derived by least squares minimization.
The fit by a power law was considered acceptable when the probability that a
value of chi-square as poor as the value found should occur by chance
was larger than 0.05.
For 5 objects in the sample (0019-0040, 0035+0040, 1625-0001, 2256+0047 and 2306+0108)
this requirement was not satisfied, so we report the
values we have obtained in Table 2, but we do not include them in the discussion.
In Fig. 4 we present the distribution of from the combined Fall and Spring sample.
The distribution is essentially confined between 0.2 and -1.1 (with one object at -1.8), with
an average spectral index of
and 1
dispersion of 0.33.
The mean was
weighted by the errors on the individual
measurements.
The median value is
.
The distribution
is not perfectly symmetric, but slightly skewed towards steeper indices.
In Fig. 4 (right panel) we also show for comparison the distribution of spectral indices derived by Ivezic et al. (2002) for about 6800 SDSS quasars with magnitude brighter than i=19, spanning a large range of redshifts (see also discussion in Richards et al. 2002).
The two distributions appear similar.
The values found for our sample are
consistent with the average power law index
derived from the composite SDSS quasar spectra, spanning a redshift range
0.04< z < 4.79 (Vanden Berk et al. 2001) which is
.
This index is valid for a large spectral range, 1216 Å
Å restframe: at longer wavelengths, the slope changes to
.
A similar result was obtained by Francis (1996) who derived
using photometric estimates, including near-IR photometry,
for a sample of quasars spanning a redshift range 0.33 to 3.67
and with a median redshift of 2.
In Fig. 4 we plot the spectral indices derived
by Francis (1996) for all the objects with redshift above 2: for these objects
the average spectral index is
(median -0.43).
Natali et al. (1998) find a similar result for a sample of bright quasars with redshift up to 2.5, with
.
However this slope is based on the continuum
shortward of the 3000 Å bump, with a much flatter index at 4000 Å. One discrepant result comes from Kuhn et al. (2001), who derived
the slopes of a sample of bright quasars
with redshift around 3, using both photometry and spectroscopy. They
find slightly flatter average spectra, with
(median -0.29); however we note that their spectral slopes for the
comparison sample of quasars are also flatter than what was found
in other studies.
![]() |
Figure 5:
The spectral index of the continuum emission: on the y axis is the
value derived by Fan et al. (2001) from the low resolution spectra, on the x-axis
the value derived from optical and near-IR photometry. The error bars represent the 1 ![]() |
Open with DEXTER |
The apparent discrepacy probably arises because the indices are
derived from different wavelength regions of the continuum
emission: the indices derived by Fan et al. (2001a) and by Schneider
et al. (2001) are from the continuum immediately blueward of the
Ly
up to 9000 Å (or less) observed emission, and thus
include only a few hundred Å in the restframe (1250 to
1600-1800 Å depending on the redshift). Furthermore, part of
the Fe complex in the 1500-2000 Å region could make the i and
z band brighter, thus producing a steepening of the spectral
indices. On the other hand our photometry spans a much larger
wavelength region and, most important, includes longer
wavelengths: at redshift 3.65 (our lower redshift) the photometry
cover from 1500 to 4700 Å (restframe) whereas at redshift 5,
our most distant object, the coverage goes from
1150 Å up to
3700 Å. Figure 3 illustrates that the continuum
immediately longward of Ly
is somewhat redder than at
longer wavelengths.
We conclude that the continuum properties of the high redshift quasars in our sample at optical restframe wavelengths are comparable to those of their lower redshift counterparts, with no significant change with epoch. We also find that the spectral slopes change somewhat depending on the wavelength regions used to measure them, as already indicated by the results of Vanden Berk et al. (2001) and Natali et al. (1998).
Acknowledgements
This paper is based on observations in the framework of the "Calar Alto Key Project for SDSS Follow-up Observations'' (Grebel 2001) obtained at the German-Spanish Astronomical Centre, Calar Alto Observatory, operated by the Max Planck Institute for Astronomy, Heidelberg jointly with the Spanish National Commission for Astronomy.
Funding for the creation and distribution of the SDSS Archive has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Aeronautics and Space Administration, the National Science Foundation, the U.S. Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society. The SDSS Web site is http://www.sdss.org/. The SDSS is managed by the Astrophysical Research Consortium (ARC) for the Participating Institutions. The Participating Institutions are The University of Chicago, Fermilab, the Institute for Advanced Study, the Japan Participation Group, The Johns Hopkins University, Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophys ics (MPA), New Mexico State University, University of Pittsburgh, Princeton University, the United States Naval Observatory, and the University of Washington. MAS acknowledges the support of NSF grant AST 00-71091