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Register a new userZ-Sequence: Photometric redshift predictions for galaxy clusters with sequential random k-nearest neighbours
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We introduce Z-Sequence, a novel empirical model that utilises photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a machine learning ensemble based on the k-nearest neighbours algorithm. We implement an automated feature selection strategy that iteratively determines appropriate combinations of filters and colours to minimise photometric redshift prediction error. We intend for Z-Sequence to be a standalone technique but it can be combined with cluster finders that do not intrinsically predict redshift, such as our own DEEP-CEE. In this proof-of-concept study we train, fine-tune and test Z-Sequence on publicly available cluster catalogues derived from the Sloan Digital Sky Survey. We determine the photometric redshift prediction error of Z-Sequence via the median value of $|Delta z|/(1+z)$ (across a photometric redshift range of $0.05 le textit{z} le 0.6$) to be $sim0.01$ when applying a small search radius. The photometric redshift prediction error for test samples increases by 30-50 per cent when the search radius is enlarged, likely due to line-of-sight interloping galaxies. Eventually, we aim to apply Z-Sequence to upcoming imaging surveys such as the Legacy Survey of Space and Time to provide photometric redshift estimates for large samples of as yet undiscovered and distant clusters.
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We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of photometric redshifts when galaxy size, ellipticity, S{e}rsic index and surface brightness are included in training on galaxy samples from the SDSS and the CFHT Stripe-82 Survey (CS82). We show that by adding galaxy morphological parameters to full $ugriz$ photometry, only mild improvements are obtained, while the gains are substantial in cases where fewer passbands are available. For instance, the combination of $grz$ photometry and morphological parameters almost fully recovers the metrics of $5$-band photometric redshifts. We demonstrate that with morphology it is possible to determine useful redshift distribution $N(z)$ of galaxy samples without any colour information. We also find that the inclusion of quasar redshifts and associated object sizes in training improves the quality of photometric redshift catalogues, compensating for the lack of a good star-galaxy separator. We further show that morphological information can mitigate biases and scatter due to bad photometry. As an application, we derive both point estimates and posterior distributions of redshifts for the official CS82 catalogue, training on morphology and SDSS Stripe-82 $ugriz$ bands when available. Our redshifts yield a 68th percentile error of $0.058(1+z)$, and a catastrophic outlier fraction of $5.2$ per cent. We further include a deep extension trained on morphology and single $i$-band CS82 photometry.
We present a multi-band analysis of the six Hubble Frontier Field clusters and their parallel fields, producing catalogs with measurements of source photometry and photometric redshifts. We release these catalogs to the public along with maps of intracluster light and models for the brightest galaxies in each field. This rich data set covers a wavelength range from 0.2 to 8 $mu m$, utilizing data from the Hubble Space Telescope, Keck Observatories, Very Large Telescope array, and Spitzer Space Telescope. We validate our products by injecting into our fields and recovering a population of synthetic objects with similar characteristics as in real extragalactic surveys. The photometric catalogs contain a total of over 32,000 entries with 50% completeness at a threshold of $mathrm{mag_{AB}}sim 29.1$ for unblended sources, and $mathrm{mag_{AB}}sim 29$ for blended ones, in the IR-Weighted detection band. Photometric redshifts were obtained by means of template fitting and have an average outlier fraction of 10.3% and scatter $sigma = 0.067$ when compared to spectroscopic estimates. The software we devised, after being tested in the present work, will be applied to new data sets from ongoing and future surveys.
We present the clustering properties of low-$z$ $(zleq1.4)$ galaxies selected by the Hyper Suprime-Cam Subaru Strategic Program Wide layer over $145$ deg$^{2}$. The wide-field and multi-wavelength observation yields $5,064,770$ galaxies at $0.3leq zleq1.4$ with photometric redshifts and physical properties. This enables the accurate measurement of angular correlation functions and subsequent halo occupation distribution (HOD) analysis allows the connection between baryonic properties and dark halo properties. The fraction of less-massive satellite galaxies at $zlesssim1$ is found to be almost constant at $sim20%$, but it gradually decreases beyond $M_{star} sim 10^{10.4}h^{-2}M_{odot}$. However, the abundance of satellite galaxies at $z>1$ is quite small even for less-massive galaxies due to the rarity of massive centrals at high-$z$. This decreasing trend is connected to the small satellite fraction of Lyman break galaxies at $z>3$. The stellar-to-halo mass ratios at $0.3leq zleq1.4$ are almost consistent with the predictions obtained using the latest empirical model; however, we identify small excesses from the theoretical model at the massive end. The pivot halo mass is found to be unchanged at $10^{11.9-12.1}h^{-1}M_{odot}$ at $0.3leq zleq1.4$, and we systematically show that $10^{12}h^{-1}M_{odot}$ is a universal pivot halo mass up to $zsim5$ that is derived using only the clustering/HOD analyses. Nevertheless, halo masses with peaked instantaneous baryon conversion efficiencies are much smaller than the pivot halo mass regardless of a redshift, and the most efficient stellar-mass assembly is thought to be in progress in $10^{11.0-11.5}h^{-1}M_{odot}$ dark haloes.
Although extensively investigated, the role of the environment in galaxy formation is still not well understood. In this context, the Galaxy Stellar Mass Function (GSMF) is a powerful tool to understand how environment relates to galaxy mass assembly and the quenching of star-formation. In this work, we make use of the high-precision photometric redshifts of the UltraVISTA Survey to study the GSMF in different environments up to $z sim 3$, on physical scales from 0.3 to 2 Mpc, down to masses of $M sim 10^{10} M_{odot}$. We witness the appearance of environmental signatures for both quiescent and star-forming galaxies. We find that the shape of the GSMF of quiescent galaxies is different in high- and low-density environments up to $z sim 2$ with the high-mass end ($M gtrsim 10^{11} M_{odot}$) being enhanced in high-density environments. On the contrary, for star-forming galaxies a difference between the GSMF in high- and low density environments is present for masses $M lesssim 10^{11} M_{odot}$. Star-forming galaxies in this mass range appear to be more frequent in low-density environments up to $z < 1.5$. Differences in the shape of the GSMF are not visible anymore at $z > 2$. Our results, in terms of general trends in the shape of the GSMF, are in agreement with a scenario in which galaxies are quenched when they enter hot gas-dominated massive haloes which are preferentially in high-density environments.
We study the slope, intercept, and scatter of the color-magnitude and color-mass relations for a sample of ten infrared red-sequence-selected clusters at z ~ 1. The quiescent galaxies in these clusters formed the bulk of their stars above z ~ 3 with an age spread {Delta}t ~ 1 Gyr. We compare UVJ color-color and spectroscopic-based galaxy selection techniques, and find a 15% difference in the galaxy populations classified as quiescent by these methods. We compare the color-magnitude relations from our red-sequence selected sample with X-ray- and photometric- redshift-selected cluster samples of similar mass and redshift. Within uncertainties, we are unable to detect any difference in the ages and star formation histories of quiescent cluster members in clusters selected by different methods, suggesting that the dominant quenching mechanism is insensitive to cluster baryon partitioning at z ~ 1.
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