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Bars are important drivers of galaxy evolution, influencing many physical processes and properties. Characterising bars is a difficult task, especially in large-scale surveys. In this work, we propose a novel morphological segmentation…

Astrophysics of Galaxies · Physics 2024-05-22 Mitchell K. Cavanagh , Kenji Bekki , Brent A. Groves

We present the first deep learning model for segmenting galactic spiral arms and bars. In a blinded assessment by expert astronomers, our predicted spiral arm masks are preferred over both current automated methods (99% of evaluations) and…

Astrophysics of Galaxies · Physics 2023-12-06 Mike Walmsley , Ashley Spindler

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because…

Instrumentation and Methods for Astrophysics · Physics 2017-06-14 D. Tuccillo , M. Huertas-Company , E. Decenciere , S. Velasco-Forero

The structural information of spiral galaxies such as the spiral arm number, offer valuable insights into their formation processes and physical roles in galaxy evolution. We developed classifiers based on CNNs using variants of the…

Astrophysics of Galaxies · Physics 2024-12-17 Ming Wei Lee , John Y. H. Soo , Syarawi M. H. Sharoni

Over the last decade it has become clear that there is a decoupling between the old stellar disk and young stellar disk in spiral galaxies. This has led to a scheme for classifying galaxies on the basis of their near-infrared morphology.…

Astrophysics · Physics 2007-05-23 M. S. Seigar , P. A. James , I. Puerari , D. L. Block

The morphology of a galaxy has been shown to encode the evolutionary history and correlates strongly with physical properties such as stellar mass, star formation rates and past merger events. While the majority of galaxies in the local…

Astrophysics of Galaxies · Physics 2023-02-23 Clár-Bríd Tohill , Steven Bamford , Christopher Conselice

In this paper, we look to analyse the spiral features of grand-design, multiarmed, and flocculent spiral galaxies using deep optical imaging from DESI Legacy Imaging Surveys. We explore the resulting distributions of various characteristics…

This paper presents some new statistical correlations between the properties of disks and spiral arms with some physical properties of galaxies. Our results show that the thickness of spiral disks tend to diminish along the Hubble sequence…

Astrophysics · Physics 2009-11-07 Jun Ma

Morphological features in galaxies, like spiral arms, bars, rings, tidal tails etc. carry information about their structure, origin and evolution. It is therefore important to catalog and study such features and to correlate them with other…

Astrophysics of Galaxies · Physics 2025-03-06 Linn Abraham , Sheelu Abraham , Ajit K. Kembhavi , N. S. Philip , A. K. Aniyan , Sudhanshu Barway , Harish Kumar

We present a method to simulate deep sky images, including realistic galaxy morphologies and telescope characteristics. To achieve a wide diversity of simulated galaxy morphologies, we first use the shapelets formalism to parametrize the…

Spiral galaxies offer a unique opportunity to study the role of star formation in galaxy evolution and to test various theoretical star formation schemes. I review some recent relevant work on the evolution of spiral galaxies. Detailed…

Astrophysics · Physics 2007-05-23 Nikos Prantzos

Edge-on galaxies have many important applications in galactic astrophysics, but they can be difficult to identify in vast amounts of astronomical data. To facilitate the search for them, we have developed a deep learning algorithm designed…

Astrophysics of Galaxies · Physics 2025-04-04 Z. Chrobakova , V. Kresnakova , R. Nagy , J. Gazdova , P. Butka

Spiral arms are the defining features of broad morphological classes of disc galaxies, but their nature and influence on galaxy evolution is still under debate. A key diagnostic for their nature is the spiral arm pattern speed: the radial…

Instrumentation and Methods for Astrophysics · Physics 2025-12-22 Robert J. J. Grand , Martin Roth

We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments and knots, according to the distribution and kinematics of dark matter (DM),…

Astrophysics of Galaxies · Physics 2022-08-03 Shigeki Inoue , Xiaotian Si , Takashi Okamoto , Moka Nishigaki

Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine Learning (mainly Deep Learning) has been called to the…

Astrophysics of Galaxies · Physics 2023-06-14 Didier Fraix-Burnet

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in…

Astrophysics of Galaxies · Physics 2024-09-23 Euclid Collaboration , B. Aussel , S. Kruk , M. Walmsley , M. Huertas-Company , M. Castellano , C. J. Conselice , M. Delli Veneri , H. Domínguez Sánchez , P. -A. Duc , U. Kuchner , A. La Marca , B. Margalef-Bentabol , F. R. Marleau , G. Stevens , Y. Toba , C. Tortora , L. Wang , N. Aghanim , B. Altieri , A. Amara , S. Andreon , N. Auricchio , M. Baldi , S. Bardelli , R. Bender , C. Bodendorf , D. Bonino , E. Branchini , M. Brescia , J. Brinchmann , S. Camera , V. Capobianco , C. Carbone , J. Carretero , S. Casas , S. Cavuoti , A. Cimatti , G. Congedo , L. Conversi , Y. Copin , F. Courbin , H. M. Courtois , M. Cropper , A. Da Silva , H. Degaudenzi , A. M. Di Giorgio , J. Dinis , F. Dubath , X. Dupac , S. Dusini , M. Farina , S. Farrens , S. Ferriol , S. Fotopoulou , M. Frailis , E. Franceschi , P. Franzetti , M. Fumana , S. Galeotta , B. Garilli , B. Gillis , C. Giocoli , A. Grazian , F. Grupp , S. V. H. Haugan , W. Holmes , I. Hook , F. Hormuth , A. Hornstrup , P. Hudelot , K. Jahnke , E. Keihänen , S. Kermiche , A. Kiessling , M. Kilbinger , B. Kubik , M. Kümmel , M. Kunz , H. Kurki-Suonio , R. Laureijs , S. Ligori , P. B. Lilje , V. Lindholm , I. Lloro , E. Maiorano , O. Mansutti , O. Marggraf , K. Markovic , N. Martinet , F. Marulli , R. Massey , S. Maurogordato , E. Medinaceli , S. Mei , Y. Mellier , M. Meneghetti , E. Merlin , G. Meylan , M. Moresco , L. Moscardini , E. Munari , S. -M. Niemi , C. Padilla , S. Paltani , F. Pasian , K. Pedersen , W. J. Percival , V. Pettorino , S. Pires , G. Polenta , M. Poncet , L. A. Popa , L. Pozzetti , F. Raison , R. Rebolo , A. Renzi , J. Rhodes , G. Riccio , E. Romelli , M. Roncarelli , E. Rossetti , R. Saglia , D. Sapone , B. Sartoris , M. Schirmer , P. Schneider , A. Secroun , G. Seidel , S. Serrano , C. Sirignano , G. Sirri , L. Stanco , J. -L. Starck , P. Tallada-Crespí , A. N. Taylor , H. I. Teplitz , I. Tereno , R. Toledo-Moreo , F. Torradeflot , I. Tutusaus , E. A. Valentijn , L. Valenziano , T. Vassallo , A. Veropalumbo , Y. Wang , J. Weller , A. Zacchei , G. Zamorani , J. Zoubian , E. Zucca , A. Biviano , M. Bolzonella , A. Boucaud , E. Bozzo , C. Burigana , C. Colodro-Conde , D. Di Ferdinando , R. Farinelli , J. Graciá-Carpio , G. Mainetti , S. Marcin , N. Mauri , C. Neissner , A. A. Nucita , Z. Sakr , V. Scottez , M. Tenti , M. Viel , M. Wiesmann , Y. Akrami , V. Allevato , S. Anselmi , C. Baccigalupi , M. Ballardini , S. Borgani , A. S. Borlaff , H. Bretonnière , S. Bruton , R. Cabanac , A. Calabro , A. Cappi , C. S. Carvalho , G. Castignani , T. Castro , G. Cañas-Herrera , K. C. Chambers , J. Coupon , O. Cucciati , S. Davini , G. De Lucia , G. Desprez , S. Di Domizio , H. Dole , A. Díaz-Sánchez , J. A. Escartin Vigo , S. Escoffier , I. Ferrero , F. Finelli , L. Gabarra , K. Ganga , J. García-Bellido , E. Gaztanaga , K. George , F. Giacomini , G. Gozaliasl , A. Gregorio , D. Guinet , A. Hall , H. Hildebrandt , A. Jimenez Munoz , J. J. E. Kajava , V. Kansal , D. Karagiannis , C. C. Kirkpatrick , L. Legrand , A. Loureiro , J. Macias-Perez , M. Magliocchetti , R. Maoli , M. Martinelli , C. J. A. P. Martins , S. Matthew , M. Maturi , L. Maurin , R. B. Metcalf , M. Migliaccio , P. Monaco , G. Morgante , S. Nadathur , Nicholas A. Walton , A. Peel , A. Pezzotta , V. Popa , C. Porciani , D. Potter , M. Pöntinen , P. Reimberg , P. -F. Rocci , A. G. Sánchez , A. Schneider , E. Sefusatti , M. Sereno , P. Simon , A. Spurio Mancini , S. A. Stanford , J. Steinwagner , G. Testera , M. Tewes , R. Teyssier , S. Toft , S. Tosi , A. Troja , M. Tucci , C. Valieri , J. Valiviita , D. Vergani , I. A. Zinchenko

The spiral structure of a spiral galaxy can be seen through different observational tracers such as the dust in the interstellar medium, the free electrons in ionized regions, the molecular gas, or the atomic hydrogen in H{\alpha} regions.…

Astrophysics of Galaxies · Physics 2022-04-20 David Felipe Barros Ramirez , Juan Carlos Muñoz-Cuartas

Stellar bars are a common morphological feature of spiral galaxies. While it is known that they can form in isolation, or be induced tidally, few studies have explored the production of stellar bars in galaxy merging. We look to investigate…

Astrophysics of Galaxies · Physics 2020-09-16 Mitchell Cavanagh , Kenji Bekki

Spiral structure can contribute significantly to a galaxy's luminosity. However, only rarely are proper photometric models of spiral arms used in decompositions. As we show in the previous work, including the spirals as a separate component…

We report an automated morphological classification of galaxies into S-wise spirals, Z-wise spirals, and non-spirals using big image data taken from Subaru/Hyper Suprime-Cam (HSC) Survey and a convolutional neural network(CNN)-based deep…

Astrophysics of Galaxies · Physics 2020-07-08 Ken-ichi Tadaki , Masanori Iye , Hideya Fukumoto , Masao Hayashi , Cristian E. Rusu , Rhythm Shimakawa , Tomoka Tosaki
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