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Accurate photometric redshifts are calculated for nearly 200,000 galaxies to a 4.5 micron flux limit of ~13 uJy in the 8.5 deg^2 Spitzer/IRAC Shallow survey. Using a hybrid photometric redshift algorithm incorporating both neural-net and template-fitting techniques, calibrated with over 15,000 spectroscopic redshifts, a redshift accuracy of sigma = 0.06(1+z) is achieved for 95% of galaxies at 0<z<1.5. The accuracy is sigma = 0.12(1+z) for 95% of AGN at 0<z<3. Redshift probability functions, central to several ongoing studies of the galaxy population, are computed for the full sample. We demonstrate that these functions accurately represent the true redshift probability density, allowing the calculation of valid confidence intervals for all objects. These probability functions have already been used to successfully identify a population of Spitzer-selected high redshift (z>1) galaxy clusters. We present one such spectroscopically confirmed cluster at <z>=1.24, ISCS J1434.5+3427. Finally, we present a measurement of the 4.5 micron-selected galaxy redshift distribution.
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The IRAC shallow survey covers 8.5 square degrees in the NOAO Deep Wide-Field Survey in Bootes with 3 or more 30 second exposures per position. An overview of the survey design, reduction, calibration, star-galaxy separation, and initial results is provided. The survey includes approximately 370,000, 280,000, 38,000, and 34,000 sources brighter than the 5 sigma limits of 6.4, 8.8, 51, and 50 microJy at 3.6, 4.5, 5.8, and 8 microns respectively, including some with unusual spectral energy distributions.
We present the SWIRE Photometric Redshift Catalogue, 1025119 redshifts of unprecedented reliability and accuracy. Our method is based on fixed galaxy and QSO templates applied to data at 0.36-4.5 mu, and on a set of 4 infrared emission templates fitted to infrared excess data at 3.6-170 mu. The code involves two passes through the data, to try to optimize recognition of AGN dust tori. A few carefully justified priors are used and are the key to supression of outliers. Extinction, A_V, is allowed as a free parameter. We use a set of 5982 spectroscopic redshifts, taken from the literature and from our own spectroscopic surveys, to analyze the performance of our method as a function of the number of photometric bands used in the solution and the reduced chi^2. For 7 photometric bands the rms value of (z_{phot}-z_{spec})/(1+z_{spec}) is 3.5%, and the percentage of catastrophic outliers is ~1%. We discuss the redshift distributions at 3.6 and 24 mu. In individual fields, structure in the redshift distribution corresponds to clusters which can be seen in the spectroscopic redshift distribution. 10% of sources in the SWIRE photometric redshift catalogue have z >2, and 4% have z>3, so this catalogue is a huge resource for high redshift galaxies. A key parameter for understanding the evolutionary status of infrared galaxies is L_{ir}/L_{opt}, which can be interpreted as the specific star-formation rate for starbursts. For dust tori around Type 1 AGN, L_{tor}/L_{opt} is a measure of the torus covering factor and we deduce a mean covering factor of 40%.
We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724 galaxies for which the spectroscopic redshift is obtained from SDSS, and magnitudes and colours are obtained from the Pan-STARRS1 Data Release 2 survey. The photometric redshift of a galaxy is then estimated by means of a local linear regression in a 5-dimensional magnitude and colour space. Our method achieves an average bias of $overline{Delta z_{rm norm}}=-2.01 times 10^{-4}$, a standard deviation of $sigma(Delta z_{rm norm})=0.0298$, and an outlier rate of $P_o=4.32%$ when cross-validating on the training set. Even though the relation between each of the Pan-STARRS1 colours and the spectroscopic redshifts is noisier than for SDSS colours, the results obtained by our method are very close to those yielded by SDSS data. The proposed method has the additional advantage of allowing the estimation of photometric redshifts on a larger portion of the sky ($sim 3/4$ vs $sim 1/3$). The training set and the code implementing this method are publicly available at www.testaddress.com.
We present the galaxy cluster autocorrelation function of 277 galaxy cluster candidates with 0.25 le z le 1.5 in a 7 deg^2 area of the IRAC Shallow Cluster Survey. We find strong clustering throughout our galaxy cluster sample, as expected for these massive structures. Specifically, at <z> = 0.5 we find a correlation length of r_0 = 17.40^{+3.98}_{-3.10} h^-1 Mpc, in excellent agreement with the Las Campanas Distant Cluster Survey, the only other non-local measurement. At higher redshift, <z> = 1, we find that strong clustering persists, with a correlation length of r_0=19.14^{+5.65}_{-4.56} h^-1 Mpc. A comparison with high resolution cosmological simulations indicates these are clusters with halo masses of sim 10^{14} Msun, a result supported by estimates of dynamical mass for a subset of the sample. In a stable clustering picture, these clusters will evolve into massive (10^{15} Msun) clusters by the present day.
We have identified 335 galaxy cluster and group candidates, 106 of which are at z > 1, using a 4.5 um selected sample of objects from a 7.25 deg^2 region in the Spitzer Infrared Array Camera (IRAC) Shallow Survey. Clusters were identified as 3-dimensional overdensities using a wavelet algorithm, based on photometric redshift probability distributions derived from IRAC and NOAO Deep Wide-Field Survey data. We estimate only ~10% of the detections are spurious. To date 12 of the z > 1 candidates have been confirmed spectroscopically, at redshifts from 1.06 to 1.41. Velocity dispersions of ~750 km/s for two of these argue for total cluster masses well above 10^14 M_sun, as does the mass estimated from the rest frame near infrared stellar luminosity. Although not selected to contain a red sequence, some evidence for red sequences is present in the spectroscopically confirmed clusters, and brighter galaxies are systematically redder than the mean galaxy color in clusters at all redshifts. The mean I - [3.6] color for cluster galaxies up to z ~ 1 is well matched by a passively evolving model in which stars are formed in a 0.1 Gyr burst starting at redshift z_f = 3. At z > 1, a wider range of formation histories is needed, but higher formation redshifts (i.e. z_f > 3) are favored for most clusters.
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