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We present a method, PhotoWeb, for estimating photometric redshifts of individual galaxies, and their equivalent distance, with megaparsec and even sub-megaparsec accuracy using the Cosmic Web as a constraint over photo-z estimates.…

Cosmology and Nongalactic Astrophysics · Physics 2015-09-30 Miguel A. Aragon-Calvo , Rien van de Weygaert , Bernard J. T. Jones , Bahram Mobasher

Cross-correlation techniques provide a promising avenue for calibrating photometric redshifts and determining redshift distributions using spectroscopy which is systematically incomplete (e.g., current deep spectroscopic surveys fail to…

Instrumentation and Methods for Astrophysics · Physics 2012-01-20 Daniel J. Matthews , Jeffrey A. Newman

We study the reliability of the statistical background subtraction method for computing the Ks-band luminosity function of cluster galaxies at z~1 using mock Red-sequence Cluster Survey cluster catalogues constructed from GALFORM…

Astrophysics · Physics 2009-11-13 Roberto P. Muñoz , Nelson D. Padilla , Luis F. Barrientos

The kSZ effect has been detected at z<1 using various techniques and data sets. The ongoing and upcoming spectroscopic galaxy surveys such as DESI and PFS will push the detection beyond z = 1, and therefore map the baryon distribution at…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-25 Ziyang Chen , Pengjie Zhang

We present accurate photometric redshifts for galaxies observed by the Cluster Lensing and Supernova survey with Hubble (CLASH). CLASH observed 25 massive galaxy cluster cores with the Hubble Space Telescope in 16 filters spanning 0.2 - 1.7…

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

In a recent study, we developed a method to model the impact of photometric redshift uncertainty on the two-point correlation function (2PCF). In this method, we can obtain both the intrinsic clustering strength and the photometric redshift…

Astrophysics of Galaxies · Physics 2021-06-29 Zhaoyu Wang , Haojie Xu , Xiaohu Yang , Yipeng Jing , Kai Wang , Hong Guo , Fuyu Dong , Min He

Powerful current and future cosmological constraints using high precision measurements of the large-scale structure of galaxies and its weak gravitational lensing effects rely on accurate characterization of the redshift distributions of…

Cosmology and Nongalactic Astrophysics · Physics 2018-12-05 Carles Sánchez , Gary M. Bernstein

The determination of galaxy merger fraction of field galaxies using automatic morphological indices and photometric redshifts is affected by several biases if observational errors are not properly treated. Here, we correct these biases…

Astrophysics · Physics 2009-11-13 C. López-Sanjuan , C. E. García-Dabó , M. Balcells

Objective: The main objective of this paper is to construct a distributed clustering algorithm based upon spatial data correlation among sensor nodes and perform data accuracy for each distributed cluster at their respective cluster head…

Networking and Internet Architecture · Computer Science 2011-08-15 Jyotirmoy Karjee , H. S Jamadagni

One of the $\textit{Euclid}$ mission's key projects is the so-called 3$\times$2pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-galaxy lensing. Although $\textit{Euclid}$ has established…

Cosmology and Nongalactic Astrophysics · Physics 2026-04-02 Euclid Collaboration , K. A. Bertmann , A. Porredon , V. Duret , J. Fonseca , H. Hildebrandt , I. Tutusaus , S. Camera , S. Escoffier , N. Aghanim , B. Altieri , A. Amara , S. Andreon , N. Auricchio , C. Baccigalupi , M. Baldi , S. Bardelli , P. Battaglia , A. Biviano , E. Branchini , M. Brescia , G. Cañas-Herrera , V. Capobianco , C. Carbone , V. F. Cardone , J. Carretero , S. Casas , F. J. Castander , M. Castellano , G. Castignani , S. Cavuoti , K. C. Chambers , A. Cimatti , C. Colodro-Conde , G. Congedo , L. Conversi , Y. Copin , F. Courbin , H. M. Courtois , M. Cropper , A. Da Silva , H. Degaudenzi , G. De Lucia , H. Dole , M. Douspis , F. Dubath , X. Dupac , S. Dusini , M. Farina , R. Farinelli , S. Farrens , S. Ferriol , F. Finelli , P. Fosalba , S. Fotopoulou , N. Fourmanoit , M. Frailis , E. Franceschi , M. Fumana , S. Galeotta , K. George , W. Gillard , B. Gillis , C. Giocoli , J. Gracia-Carpio , A. Grazian , F. Grupp , S. V. H. Haugan , H. Hoekstra , W. Holmes , F. Hormuth , A. Hornstrup , K. Jahnke , M. Jhabvala , B. Joachimi , S. Kermiche , A. Kiessling , M. Kilbinger , B. Kubik , M. Kunz , H. Kurki-Suonio , A. M. C. Le Brun , S. Ligori , P. B. Lilje , V. Lindholm , I. Lloro , G. Mainetti , D. Maino , E. Maiorano , O. Mansutti , S. Marcin , O. Marggraf , M. Martinelli , N. Martinet , F. Marulli , R. J. Massey , E. Medinaceli , S. Mei , Y. Mellier , M. Meneghetti , E. Merlin , G. Meylan , A. Mora , M. Moresco , L. Moscardini , R. Nakajima , C. Neissner , S. -M. Niemi , J. W. Nightingale , C. Padilla , S. Paltani , F. Pasian , K. Pedersen , W. J. Percival , V. Pettorino , G. Polenta , M. Poncet , L. A. Popa , L. Pozzetti , F. Raison , A. Renzi , J. Rhodes , G. Riccio , E. Romelli , M. Roncarelli , C. Rosset , R. Saglia , Z. Sakr , D. Sapone , B. Sartoris , P. Schneider , T. Schrabback , A. Secroun , E. Sefusatti , G. Seidel , E. Sihvola , P. Simon , C. Sirignano , G. Sirri , A. Spurio Mancini , L. Stanco , P. Tallada-Crespí , A. N. Taylor , I. Tereno , N. Tessore , S. Toft , R. Toledo-Moreo , F. Torradeflot , J. Valiviita , T. Vassallo , G. Verdoes Kleijn , Y. Wang , J. Weller , G. Zamorani , F. M. Zerbi , E. Zucca , M. Ballardini , A. Boucaud , E. Bozzo , C. Burigana , R. Cabanac , M. Calabrese , A. Cappi , T. Castro , J. A. Escartin Vigo , G. Fabbian , J. Macias-Perez , R. Maoli , J. Martín-Fleitas , N. Mauri , R. B. Metcalf , P. Monaco , A. A. Nucita , A. Pezzotta , M. Pöntinen , I. Risso , V. Scottez , M. Sereno , M. Tenti , M. Tucci , M. Viel , M. Wiesmann , Y. Akrami , I. T. Andika , G. Angora , S. Anselmi , M. Archidiacono , F. Atrio-Barandela , L. Bazzanini , D. Bertacca , M. Bethermin , F. Beutler , A. Blanchard , L. Blot , M. Bonici , S. Borgani , M. L. Brown , S. Bruton , A. Calabro , B. Camacho Quevedo , F. Caro , C. S. Carvalho , F. Cogato , S. Conseil , A. R. Cooray , S. Davini , G. Desprez , A. Díaz-Sánchez , S. Di Domizio , J. M. Diego , M. Y. Elkhashab , A. Enia , Y. Fang , A. G. Ferrari , A. Finoguenov , F. Fontanot , A. Franco , K. Ganga , T. Gasparetto , E. Gaztanaga , F. Giacomini , F. Gianotti , G. Gozaliasl , A. Gruppuso , M. Guidi , C. M. Gutierrez , A. Hall , C. Hernández-Monteagudo , J. Hjorth , S. Joudaki , J. J. E. Kajava , Y. Kang , V. Kansal , D. Karagiannis , K. Kiiveri , J. Kim , C. C. Kirkpatrick , S. Kruk , M. Lattanzi , L. Legrand , M. Lembo , F. Lepori , G. Leroy , G. F. Lesci , J. Lesgourgues , T. I. Liaudat , S. J. Liu , M. Magliocchetti , A. Manjón-García , F. Mannucci , C. J. A. P. Martins , M. Migliaccio , M. Miluzio , A. Montoro , C. Moretti , G. Morgante , S. Nadathur , A. Navarro-Alsina , S. Nesseris , L. Pagano , D. Paoletti , F. Passalacqua , K. Paterson , L. Patrizii , A. Pisani , D. Potter , G. W. Pratt , S. Quai , M. Radovich , K. Rojas , W. Roster , S. Sacquegna , D. B. Sanders , E. Sarpa , A. Schneider , M. Schultheis , D. Sciotti , E. Sellentin , L. C. Smith , K. Tanidis , C. Tao , F. Tarsitano , G. Testera , R. Teyssier , S. Tosi , A. Troja , A. Venhola , D. Vergani , F. Vernizzi , G. Verza , S. Vinciguerra , N. A. Walton , A. H. Wright

Clustering is the task of gathering similar data samples into clusters without using any predefined labels. It has been widely studied in machine learning literature, and recent advancements in deep learning have revived interest in this…

Machine Learning · Computer Science 2023-09-04 Mohammadreza Sadeghi , Hadi Hojjati , Narges Armanfard

This work emphasizes that heterogeneity, diversity, discontinuity, and discreteness in data is to be exploited in classification and regression problems. A global a priori model may not be desirable. For data analytics in cosmology, this is…

Instrumentation and Methods for Astrophysics · Physics 2018-04-10 Fionn Murtagh

We present a study of photometric redshift accuracy in the 3D-HST photometric catalogs, using 3D-HST grism redshifts to quantify and dissect trends in redshift accuracy for galaxies brighter than $H_{F140W}<24$ with an unprecedented and…

Contamination of interloper galaxies due to misidentified emission lines can be a big issue in the spectroscopic galaxy clustering surveys, especially in future high-precision observations. We propose a statistical method based on the…

Cosmology and Nongalactic Astrophysics · Physics 2021-10-14 Yan Gong , Haitao Miao , Pengjie Zhang , Xuelei Chen

We present simulations of the cluster distribution in several dark matter models, using an optimized version of the truncated Zel'dovich approximation (TZA). We compare them with N-body cluster simulations and find that the TZA provides a…

Astrophysics · Physics 2015-06-24 S. Borgani , M. Plionis , P. Coles , L. Moscardini

In the modern galaxy surveys photometric redshifts play a central role in a broad range of studies, from gravitational lensing and dark matter distribution to galaxy evolution. Using a dataset of about 25,000 galaxies from the second data…

Instrumentation and Methods for Astrophysics · Physics 2017-06-14 Stefano Cavuoti , Crescenzo Tortora , Massimo Brescia , Giuseppe Longo , Mario Radovich , Nicola R. Napolitano , Valeria Amaro , Civita Vellucci

We present the calibration of the Dark Energy Survey Year 1 (DES Y1) weak lensing source galaxy redshift distributions from clustering measurements. By cross-correlating the positions of source galaxies with luminous red galaxies selected…

Aims: We present a custom support vector machine classification package for photometric redshift estimation, including comparisons with other methods. We also explore the efficacy of including galaxy shape information in redshift…

Instrumentation and Methods for Astrophysics · Physics 2017-04-12 Evan Jones , J. Singal

Accurate redshift estimates are a vital component in understanding galaxy evolution and precision cosmology. In this paper, we explore approaches to increase the applicability of machine learning models for photometric redshift estimation…

Instrumentation and Methods for Astrophysics · Physics 2026-01-27 Jonathan Soriano , Tuan Do , Srinath Saikrishnan , Vikram Seenivasan , Bernie Boscoe , Jack Singal , Evan Jones