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We review the use of photometric redshifts in the particular context of Gravitational Telescopes. We discuss on the possible application of such a technique to the study of both the faint population of distant sources and the properties of…

Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of…

Instrumentation and Methods for Astrophysics · Physics 2022-03-09 Ben Henghes , Connor Pettitt , Jeyan Thiyagalingam , Tony Hey , Ofer Lahav

Spectral clustering is a novel clustering method which can detect complex shapes of data clusters. However, it requires the eigen decomposition of the graph Laplacian matrix, which is proportion to $O(n^3)$ and thus is not suitable for…

Machine Learning · Computer Science 2013-07-02 Nguyen Lu Dang Khoa , Sanjay Chawla

Gamma-ray bursts (GRBs) are spectacularly energetic events, with the potential to inform on the early universe and its evolution, once their redshifts are known. Unfortunately, determining redshifts is a painstaking procedure requiring…

Photometric redshift estimation plays a crucial role in modern cosmological surveys for studying the universe's large-scale structures and the evolution of galaxies. Deep learning has emerged as a powerful method to produce accurate…

Cosmology and Nongalactic Astrophysics · Physics 2023-10-04 R. Ait-Ouahmed , S. Arnouts , J. Pasquet , M. Treyer , E. Bertin

We present a new algorithm, CAMIRA, to identify clusters of galaxies in wide-field imaging survey data. We base our algorithm on the stellar population synthesis model to predict colours of red-sequence galaxies at a given redshift for an…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Masamune Oguri

Precision photometric redshifts will be essential for extracting cosmological parameters from the next generation of wide-area imaging surveys. In this paper we introduce a photometric redshift algorithm, ArborZ, based on the…

Cosmology and Nongalactic Astrophysics · Physics 2010-05-06 David W. Gerdes , Adam J. Sypniewski , Timothy A. McKay , Jiangang Hao , Matthew R. Weis , Risa H. Wechsler , Michael T. Busha

More than 150 galaxies have been detected in blank-field millimetre and sub-millimetre surveys. However the redshift distribution of sub-mm galaxies remains uncertain due to the difficulty in identifying their optical-IR counterparts, and…

Astrophysics · Physics 2010-12-13 Itziar Aretxaga , David H. Hughes , Edward Chapin , Enrique Gaztanaga

The color-magnitude relation (CMR) of early-type galaxies in clusters provides a powerful tool for finding clusters and determining photometric redshifts for clusters using two-filter imaging data. We demonstrate the high accuracy of…

Astrophysics · Physics 2007-05-23 H. K. C. Yee , M. D. Gladders , O. Lopez-Cruz

Photometric redshifts are studied with a template approach using data from HDF-N and -S . The problem of aliasing in photometric redshift estimates is investigated in some detail and found not to be a significant problem if at least four…

Astrophysics · Physics 2009-11-10 Michael Rowan-Robinson

Much of the science that is made possible by multiwavelength redshift surveys requires the use of photometric redshifts. But as these surveys become more ambitious, and as we seek to perform increasingly accurate measurements, it becomes…

Cosmology and Nongalactic Astrophysics · Physics 2010-11-23 Ryan F. Quadri , Rik J. Williams

Wide-field optical imaging surveys are efficient at identifying galaxy clusters, but optically identified clusters suffer from projection effects--physically unassociated galaxies along the line of sight can be misidentified as cluster…

Cosmology and Nongalactic Astrophysics · Physics 2026-04-02 Lei Yang , Hao-Yi Wu , Tesla Jeltema , Chun-Hao To , Ross Cawthon , Shulei Cao

Despite the advances provided by large-scale photometric surveys, stellar features - such as metallicity - generally remain limited to spectroscopic observations often of bright, nearby low-extinction stars. To rectify this, we present a…

Astrophysics of Galaxies · Physics 2022-10-19 Connor P. Fallows , Jason L. Sanders

Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a…

Astrophysics · Physics 2009-10-31 R. J. Brunner , A. J. Connolly , A. S. Szalay

We calculate photometric redshifts from the Sloan Digital Sky Survey Main Galaxy Sample, The Galaxy Evolution Explorer All Sky Survey, and The Two Micron All Sky Survey using two new training-set methods. We utilize the broad-band…

Astrophysics · Physics 2008-11-26 M. J. Way , A. N. Srivastava

The development of the state-of-the-art telescopic systems capable of performing expansive sky surveys such as the Sloan Digital Sky Survey, Euclid, and the Rubin Observatory's Legacy Survey of Space and Time (LSST) has significantly…

A method of obtaining approximate redshifts and spectral types of galaxies using a photometric system of six broad-bandpass filters is developed. The technique utilizes a smallest maximum difference approach rather than a least-squares…

Astrophysics · Physics 2009-10-30 Charles T. Liu , Richard F. Green

The Red-Sequence Cluster Survey (RCS) provides a large and deep photometric catalog of galaxies in the $z'$ and $R_c$ bands for ~90 square degrees of sky, and supplemental $V$ and $B$ data have been obtained for 33.6 deg$^{2}$. We compile a…

Astrophysics · Physics 2009-11-10 B. C. Hsieh , H. K. C. Yee , H. Lin , M. D. Gladders

We introduce Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), a proof of concept for a novel deep learning technique, applied directly to wide-field colour imaging to search for galaxy clusters, without the need for…

Astrophysics of Galaxies · Physics 2019-11-26 Matthew C. Chan , John P. Stott

The increasing needs of clustering massive datasets and the high cost of running clustering algorithms poses difficult problems for users. In this context it is important to determine if a data set is clusterable, that is, it may be…

Machine Learning · Computer Science 2020-01-08 Dan Simovici , Kaixun Hua