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Deconvolutional layers have been widely used in a variety of deep models for up-sampling, including encoder-decoder networks for semantic segmentation and deep generative models for unsupervised learning. One of the key limitations of…

Machine Learning · Computer Science 2017-11-28 Hongyang Gao , Hao Yuan , Zhengyang Wang , Shuiwang Ji

Galaxy surveys probe both structure formation and the expansion rate, making them promising avenues for understanding the dark universe. Photometric surveys accurately map the 2D distribution of galaxy positions and shapes in a given…

Cosmology and Nongalactic Astrophysics · Physics 2017-06-19 Samuel Passaglia , Alessandro Manzotti , Scott Dodelson

We present DECORAS, a deep learning based approach to detect both point and extended sources from Very Long Baseline Interferometry (VLBI) observations. Our approach is based on an encoder-decoder neural network architecture that uses a low…

Instrumentation and Methods for Astrophysics · Physics 2022-07-25 S. Rezaei , J. P. McKean , M. Biehl , A. Javadpour

To train a deblurring network, an appropriate dataset with paired blurry and sharp images is essential. Existing datasets collect blurry images either synthetically by aggregating consecutive sharp frames or using sophisticated camera…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Dongwoo Lee , Joonkyu Park , Kyoung Mu Lee

The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass…

Instrumentation and Methods for Astrophysics · Physics 2022-03-30 Sheng-Chieh Lin , Yuanyuan Su , Gongbo Liang , Yuanyuan Zhang , Nathan Jacobs , Yu Zhang

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source…

Beyond the commonly recognized optical aberrations, the imaging performance of simplified optical systems--including single-lens and metalens designs--is often further degraded by veiling glare caused by stray-light scattering from…

Image and Video Processing · Electrical Eng. & Systems 2026-03-09 Xiaolong Qian , Qi Jiang , Lei Sun , Zongxi Yu , Kailun Yang , Peixuan Wu , Jiacheng Zhou , Yao Gao , Yaoguang Ma , Ming-Hsuan Yang , Kaiwei Wang

Photometric redshifts (photo-$z$'s) are crucial for the cosmology, galaxy evolution, and transient science drivers of next-generation imaging facilities like the Euclid Mission, the Rubin Observatory, and the Nancy Grace Roman Space…

Astrophysics of Galaxies · Physics 2025-12-03 Emma R. Moran , Brett H. Andrews , Jeffrey A. Newman , Biprateep Dey

We are presenting a novel, Deep Learning based approach to estimate the normalized broadband spectral energy distribution (SED) of different stellar populations in synthetic galaxies. In contrast to the non-parametric multiband source…

Instrumentation and Methods for Astrophysics · Physics 2022-02-16 Sándor Kunsági-Máté , István Csabai

Studies have shown that the morphologies of galaxies are substantially transformed following coalescence after a merger, but post-mergers are notoriously difficult to identify, especially in imaging that is shallow or low-resolution. We…

Astrophysics of Galaxies · Physics 2024-09-26 Robert W. Bickley , Scott Wilkinson , Leonardo Ferreira , Sara L. Ellison , Connor Bottrell , Debarpita Jyoti

The formation and evolution of ring structures in galaxies are crucial for understanding the nature and distribution of dark matter, galactic interactions, and the internal secular evolution of galaxies. However, the limited number of…

Astrophysics of Galaxies · Physics 2025-06-23 Aina Zhang , Xiaoming Kong , Bowen Liu , Nan Li , Yude Bu , Zhenping Yi , Meng Liu

Calibrating the photometric redshifts of >10^9 galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. The path to obtaining the required spectroscopic redshifts for training and…

Extragalactic surveys provide significant statistical data for the study of crucial galaxy parameters used to constrain galaxy evolution, e.g. stellar mass (M$_*$) and star formation rate (SFR), under different environmental conditions.…

Astrophysics of Galaxies · Physics 2024-06-12 Paula Calderón-Castillo , Neil M. Nagar , Sukyoung Yi , Yu-Yen Chang , Roger Leiton , Thomas M. Hughes

Recovering sharper images from blurred observations, referred to as deconvolution, is an ill-posed problem where classical approaches often produce unsatisfactory results. In ground-based astronomy, combining multiple exposures to achieve…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Fausto Navarro , Daniel Hall , Tamas Budavari , Yashil Sukurdeep

Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most…

Astrophysics of Galaxies · Physics 2023-01-05 Euclid Collaboration , L. Bisigello , C. J. Conselice , M. Baes , M. Bolzonella , M. Brescia , S. Cavuoti , O. Cucciati , A. Humphrey , L. K. Hunt , C. Maraston , L. Pozzetti , C. Tortora , S. E. van Mierlo , N. Aghanim , N. Auricchio , M. Baldi , R. Bender , C. Bodendorf , D. Bonino , E. Branchini , J. Brinchmann , S. Camera , V. Capobianco , C. Carbone , J. Carretero , F. J. Castander , M. Castellano , A. Cimatti , G. Congedo , L. Conversi , Y. Copin , L. Corcione , F. Courbin , M. Cropper , A. Da Silva , H. Degaudenzi , M. Douspis , F. Dubath , C. A. J. Duncan , X. Dupac , S. Dusini , S. Farrens , S. Ferriol , M. Frailis , E. Franceschi , P. Franzetti , M. Fumana , B. Garilli , W. Gillard , B. Gillis , C. Giocoli , A. Grazian , F. Grupp , L. Guzzo , S. V. H. Haugan , W. Holmes , F. Hormuth , A. Hornstrup , K. Jahnke , M. Kümmel , S. Kermiche , A. Kiessling , M. Kilbinger , R. Kohley , M. Kunz , H. Kurki-Suonio , S. Ligori , P. B. Lilje , I. Lloro , E. Maiorano , O. Mansutti , O. Marggraf , K. Markovic , F. Marulli , R. Massey , S. Maurogordato , E. Medinaceli , M. Meneghetti , E. Merlin , G. Meylan , M. Moresco , L. Moscardini , E. Munari , S. M. Niemi , C. Padilla , S. Paltani , F. Pasian , K. Pedersen , V. Pettorino , G. Polenta , M. Poncet , L. Popa , F. Raison , A. Renzi , J. Rhodes , G. Riccio , H. -W. Rix , E. Romelli , M. Roncarelli , C. Rosset , E. Rossetti , R. Saglia , D. Sapone , B. Sartoris , P. Schneider , M. Scodeggio , A. Secroun , G. Seidel , C. Sirignano , G. Sirri , L. Stanco , P. Tallada-Crespí , D. Tavagnacco , A. N. Taylor , I. Tereno , R. Toledo-Moreo , F. Torradeflot , I. Tutusaus , E. A. Valentijn , L. Valenziano , T. Vassallo , Y. Wang , A. Zacchei , G. Zamorani , J. Zoubian , S. Andreon , S. Bardelli A. Boucaud , C. Colodro-Conde , D. Di Ferdinando , J. Graciá-Carpio , V. Lindholm , D. Maino , S. Mei , V. Scottez , F. Sureau , M. Tenti , E. Zucca , A. S. Borlaff , M. Ballardini , A. Biviano , E. Bozzo , C. Burigana , R. Cabanac , A. Cappi , C. S. Carvalho , S. Casas , G. Castignani , A. Cooray , J. Coupon , H. M. Courtois , J. Cuby , S. Davini , G. De Lucia , G. Desprez , H. Dole , J. A. Escartin , S. Escoffier , M. Farina , S. Fotopoulou , K. Ganga , J. Garcia-Bellido , K. George , F. Giacomini , G. Gozaliasl , H. Hildebrandt , I. Hook , M. Huertas-Company , V. Kansal , E. Keihanen , C. C. Kirkpatrick , A. Loureiro , J. F. Macías-Pérez , M. Magliocchetti , G. Mainetti , S. Marcin , M. Martinelli , N. Martinet , R. B. Metcalf , P. Monaco , G. Morgante , S. Nadathur , A. A. Nucita , L. Patrizii , A. Peel , D. Potter , A. Pourtsidou , M. Pöntinen , P. Reimberg , A. G. Sánchez , Z. Sakr , M. Schirmer , E. Sefusatti , M. Sereno , J. Stadel , R. Teyssier , C. Valieri , J. Valiviita , M. Viel

With the advent of future big-data surveys, automated tools for unsupervised discovery are becoming ever more necessary. In this work, we explore the ability of deep generative networks for detecting outliers in astronomical imaging…

Weak gravitational lensing is a powerful probe for constraining cosmological parameters, but its success relies on accurate shear measurements. In this paper, we use image simulations to investigate how a joint analysis of high-resolution…

Cosmology and Nongalactic Astrophysics · Physics 2025-10-22 Shiyang Zhang , Shun-Sheng Li , Henk Hoekstra

Overcoming both modeling and computational challenges, we present, for the first time, the extended surface-brightness distribution model of a strongly-lensed source in a complex galaxy-cluster-scale system. We exploit the high-resolution…

We perform a comprehensive study of the total mass distribution of the galaxy cluster RXCJ2248 ($z=0.348$) with a set of high-precision strong lensing models, which take advantage of extensive spectroscopic information on many multiply…