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Register a new userGalaxy Clusters at 0.9<z<1.7 in the AKARI NEP deep field
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Authors
Tomotsugu Goto
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There is a huge gap between properties of red-sequence selected massive galaxy clusters at z<1 and Lyman-break selected proto-clusters at z>3. It is important to understand when and how the z>3 proto-clusters evolve into passive clusters at z<1. We aim to fill this cluster desert by using the space-based N4(4um) imaging with the AKARI. The z-N4 color is a powerful separator of cluster galaxies at z>1, taking advantage of the 4000A break and the 1.6um bump. We carefully selected 16 promising cluster candidates at 0.9<z<1.7, which all show obvious over-density of galaxies and a prominent red-sequence. At this redshift range, the mid-infrared S15um/S9um flux ratio is an extinction-free indicator of galaxy star formation activity due to the redshifted PAH emission lines (6.2,7.7 and 8.6um). We show statistically that the cluster galaxies have a lower S15um/S9um flux ratio than field galaxies, i.e., cluster galaxies already have lower star-formation activity at 0.9<z<1.7, pushing the formation epoch of these galaxy clusters to a higher redshift.
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Context: It is crucial to develop a method for classifying objects detected in deep surveys at infrared wavelengths. We specifically need a method to separate galaxies from stars using only the infrared information to study the properties of galaxies, e.g., to estimate the angular correlation function, without introducing any additional bias. Aims. We aim to separate stars and galaxies in the data from the AKARI North Ecliptic Pole (NEP) Deep survey collected in nine AKARI / IRC bands from 2 to 24 {mu}m that cover the near- and mid-infrared wavelengths (hereafter NIR and MIR). We plan to estimate the correlation function for NIR and MIR galaxies from a sample selected according to our criteria in future research. Methods: We used support vector machines (SVM) to study the distribution of stars and galaxies in the AKARIs multicolor space. We defined the training samples of these objects by calculating their infrared stellarity parameter (sgc). We created the most efficient classifier and then tested it on the whole sample. We confirmed the developed separation with auxiliary optical data obtained by the Subaru telescope and by creating Euclidean normalized number count plots. Results: We obtain a 90% accuracy in pinpointing galaxies and 98% accuracy for stars in infrared multicolor space with the infrared SVM classifier. The source counts and comparison with the optical data (with a consistency of 65% for selecting stars and 96% for galaxies) confirm that our star/galaxy separation methods are reliable. Conclusions: The infrared classifier derived with the SVM method based on infrared sgc- selected training samples proves to be very efficient and accurate in selecting stars and galaxies in deep surveys at infrared wavelengths carried out without any previous target object selection.
We present a preliminary analysis of clustering of galaxies luminous in the near- and mid-infrared as seen by seven various ilters of the AKARI IRC instrument from 2 $mu$m to 24 $mu$m in the the AKARI NEP-Deep field. We compare populations of galaxies detected in different filters and their clustering properties. We conclude that different AKARI filters allow to trace different populations composed mainly of star-forming galaxies located in different environments. In particular, the mid-infrared filters at redshift z $sim$ 0.8 and higher trace a population of strongly evolving galaxies located in massive haloes which might have ended as elliptical galaxies today.
The aim of this work is to create a new catalog of reliable AGN candidates selected from the AKARI NEP-Deep field. Selection of the AGN candidates was done by applying a fuzzy SVM algorithm, which allows to incorporate measurement uncertainties into the classification process. The training dataset was based on the spectroscopic data available for selected objects in the NEP-Deep and NEP-Wide fields. The generalization sample was based on the AKARI NEP-Deep field data including objects without optical counterparts and making use of the infrared information only. A high quality catalog of previously unclassified 275 AGN candidates was prepared.
We present the evolution of the color-magnitude distribution of galaxy clusters from z = 0.45 to z = 0.9 using a homogeneously selected sample of ~1000 clusters drawn from the Red-Sequence Cluster Survey (RCS). The red fraction of galaxies decreases as a function of increasing redshift for all cluster-centric radii, consistent with the Butcher-Oemler effect, and suggesting that the cluster blue population may be identified with newly infalling galaxies. We also find that the red fraction at the core has a shallower evolution compared with that at the cluster outskirts. Detailed examination of the color distribution of blue galaxies suggests that they have colors consistent with normal spirals and may redden slightly with time. Galaxies of starburst spectral type contribute less than 5% of the increase in the blue population at high redshift, implying that the observed Butcher-Oemler effect is not caused by a unobscured starbursts, but is more consistent with a normal coeval field population.
We present a method of selection of 24~$mu$m galaxies from the AKARI North Ecliptic Pole (NEP) Deep Field down to $150 mbox{ }mu$Jy and measurements of their two-point correlation function. We aim to associate various 24 $mu$m selected galaxy populations with present day galaxies and to investigate the impact of their environment on the direction of their subsequent evolution. We discuss using of Support Vector Machines (SVM) algorithm applied to infrared photometric data to perform star-galaxy separation, in which we achieve an accuracy higher than 80%. The photometric redshift information, obtained through the CIGALE code, is used to explore the redshift dependence of the correlation function parameter ($r_{0}$) as well as the linear bias evolution. This parameter relates galaxy distribution to the one of the underlying dark matter. We connect the investigated sources to their potential local descendants through a simplified model of the clustering evolution without interactions. We observe two different populations of star-forming galaxies, at $z_{med}sim 0.25$, $z_{med}sim 0.9$. Measurements of total infrared luminosities ($L_{TIR}$) show that the sample at $z_{med}sim 0.25$ is composed mostly of local star-forming galaxies, while the sample at $z_{med}sim0.9$ is composed of luminous infrared galaxies (LIRGs) with $L_{TIR}sim 10^{11.62}L_{odot}$. We find that dark halo mass is not necessarily correlated with the $L_{TIR}$: for subsamples with $L_{TIR}= 10^{11.15} L_{odot}$ at $z_{med}sim 0.7$ we observe a higher clustering length ($r_{0}=6.21pm0.78$ $[h^{-1} mbox{Mpc}]$) than for a subsample with mean $L_{TIR}=10^{11.84} L_{odot}$ at $z_{med}sim1.1$ ($r_{0}=5.86pm0.69$ $h^{-1} mbox{Mpc}$). We find that galaxies at $z_{med}sim 0.9$ can be ancestors of present day $L_{*}$ early type galaxies, which exhibit a very high $r_{0}sim 8$~$h^{-1} mbox{Mpc}$.
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