Identifying galaxy mergers in observations and simulations with deep learning
A&A, 626 (2019) A49
Published online: 2019-06-12
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
The Lyα and Continuum Origins Survey. III. Investigating the Link between Galaxy Morphology, Merger Properties, and LyC Escape
Alexandra Le Reste, Anne E. Jaskot, Jordanne Brazie, Claudia Scarlata, Sophia R. Flury, Kameswara B. Mantha, Alaina Henry, Matthew J. Hayes, Göran Östlin, Alberto Saldana-Lopez, Trinh X. Thuan, Maxime Trebitsch, Xinfeng Xu, Ricardo O. Amorín, Cody A. Carr, Floriane Leclercq, Daniel Schaerer, Aaron Smith, Jens Melinder, M. S. Oey, Swara Ravindranath, Michael Rutkowski and Bingjie WangThe Astrophysical Journal 998 (2) 222 (2026)
https://doi.org/10.3847/1538-4357/ae2ad8
Tracing the AGN–merger connection: insights from cosmological simulations and JWST mock observations
Hannah Jhee, Ena Choi, Rachel S Somerville, Dale D Kocevski, Michaela Hirschmann, Thorsten Naab, Desika Narayanan, Intae Jung and Juhan KimMonthly Notices of the Royal Astronomical Society 548 (2) (2026)
https://doi.org/10.1093/mnras/stag435
Half a Million Binary Stars Identified from the Low-resolution Spectra of LAMOST
Yingjie Jing, Tian-Xiang Mao, Jie Wang, Chao Liu and Xiaodian ChenThe Astrophysical Journal Supplement Series 277 (1) 15 (2025)
https://doi.org/10.3847/1538-4365/ada895
Machine learning the gap between real and simulated nebulae
Francesco Belfiore, Michele Ginolfi, Guillermo Blanc, Mederic Boquien, Melanie Chevance, Enrico Congiu, Simon C. O. Glover, Brent Groves, Ralf S. Klessen, J. Eduardo Méndez-Delgado and Thomas G. WilliamsAstronomy & Astrophysics 694 A212 (2025)
https://doi.org/10.1051/0004-6361/202451934
The dependence of the intracluster light fraction on galaxy cluster properties
Louisa Canepa, Sarah Brough, Mireia Montes and Nina HatchMonthly Notices of the Royal Astronomical Society 545 (3) (2025)
https://doi.org/10.1093/mnras/staf2167
Identifying astrophysical anomalies in 99.6 million source cutouts from the Hubble legacy archive using AnomalyMatch
David O’Ryan and Pablo GómezAstronomy & Astrophysics 704 A227 (2025)
https://doi.org/10.1051/0004-6361/202555512
Observationally derived change in the star formation rate as mergers progress
W. J. Pearson, L. Wang, V. Rodriguez-Gomez, B. Margalef-Bentabol and L. E. SuelvesAstronomy & Astrophysics 704 A234 (2025)
https://doi.org/10.1051/0004-6361/202453228
STRRINGS: STReams in Residual Images of Nearby GalaxieS
Elisabeth Sola, David Chemaly, Vasily Belokurov, Oliver Müller, Anke Ardern-Arentsen, Elliot Y Davies, Júlia Laguna-Miralles, GyuChul Myeong, Konstantinos Panagiotakis, HanYuan Zhang, Denis Erkal, Sergey E Koposov, Dustin Lang and Jacob NibauerMonthly Notices of the Royal Astronomical Society 544 (1) 735 (2025)
https://doi.org/10.1093/mnras/staf1647
Interacting galaxies in the IllustrisTNG simulations – IX: Mini mergers trigger AGNs in cosmological simulations
Shoshannah Byrne-Mamahit, Sara L Ellison, David R Patton, Scott Wilkinson, Leonardo Ferreira and Connor BottrellMonthly Notices of the Royal Astronomical Society 544 (2) 1673 (2025)
https://doi.org/10.1093/mnras/staf1765
Unions with UNIONS: Using Galaxy–Galaxy Lensing to Probe Galaxy Mergers
Isaac Cheng, Jack Elvin-Poole, Michael J. Hudson, Ruxin Barré, Sara L. Ellison, Robert W. Bickley, Thomas J. L. de Boer, Sébastien Fabbro, Leonardo Ferreira, Sacha Guerrini, Fabian Hervas Peters, Hendrik Hildebrandt, Martin Kilbinger, Alan W. McConnachie, Ludovic van Waerbeke and Anna WittjeThe Astrophysical Journal 992 (2) 171 (2025)
https://doi.org/10.3847/1538-4357/ae03b8
Streams and shells decoded: A density-driven approach to stellar clustering in galactic halos with AstroLink
Viraj Ekanayaka, Smrithi Gireesh Babu, William Oliver and Geraint LewisPublications of the Astronomical Society of Australia 42 (2025)
https://doi.org/10.1017/pasa.2025.10077
Analysing the prevalence of tidal features in HSC-SSP using self-supervised representation learning
A Desmons, S Brough, F Lanusse, L Canepa and A KhalidMonthly Notices of the Royal Astronomical Society 543 (3) 2255 (2025)
https://doi.org/10.1093/mnras/staf1617
Recent Research Progress on Galaxy Pairs and Mergers with JWST Observations
Tong Yi-lu and Dai YuChinese Astronomy and Astrophysics 49 (3) 493 (2025)
https://doi.org/10.1016/j.chinastron.2025.09.008
GalaxyGenius: Mock galaxy image generator for various telescopes from hydrodynamical simulations
Xingchen Zhou, Hang Yang, Nan Li, Qi Xiong, Furen Deng, Xian-Min Meng, Renhao Ye, Shiyin Shen, Peng Wei, Qifan Cui, Zizhao He, Ayodeji Ibitoye, Chengliang Wei and Yuedong FangAstronomy & Astrophysics 700 A120 (2025)
https://doi.org/10.1051/0004-6361/202554287
Low surface brightness structures from annotated deep CFHT images: effects of the host galaxy’s properties and environment
Elisabeth Sola, Pierre-Alain Duc, Mathias Urbano, Felix Richards, Adeline Paiement, Michal Bílek, Mustafa K Yıldız, Alessandro Boselli, Patrick Côté, Jean-Charles Cuillandre, Laura Ferrarese, Stephen Gwyn, Olivier Marchal, Alan W McConnachie, Matthieu Baumann, Thomas Boch, Florence Durret, Matteo Fossati, Rebecca Habas, Francine R Marleau, Oliver Müller, Mélina Poulain and Vasily BelokurovMonthly Notices of the Royal Astronomical Society 541 (4) 3015 (2025)
https://doi.org/10.1093/mnras/staf1139
What drives the growth of black holes: A decade of progress
D.M. Alexander, R.C. Hickox, J. Aird, F. Combes, T. Costa, M. Habouzit, C.M. Harrison, R.I. Leng, L.K. Morabito, S.L. Uckelman and P. VickersNew Astronomy Reviews 101 101733 (2025)
https://doi.org/10.1016/j.newar.2025.101733
Galaxy Morphology Classification via Deep Semisupervised Learning with Limited Labeled Data
Zhijian Luo, Jianzhen Chen, Zhu Chen, Shaohua Zhang, Liping Fu, Hubing Xiao and Chenggang ShuThe Astrophysical Journal Supplement Series 279 (1) 17 (2025)
https://doi.org/10.3847/1538-4365/addb4c
Classifying merger stages with adaptive deep learning and cosmological hydrodynamical simulations
Rosa de Graaff, Berta Margalef-Bentabol, Lingyu Wang, Antonio La Marca, William J. Pearson, Vicente Rodriguez-Gomez and Mike WalmsleyAstronomy & Astrophysics 697 A207 (2025)
https://doi.org/10.1051/0004-6361/202452659
Time-scales for the effects of interactions on galaxy properties and SMBH growth
David O’Ryan, Brooke D Simmons, Andreas L Faisst, Izzy L Garland, Tobias Géron, Ghassem Gozaliasl, Steven Gillman, Sofia Guedes Vaz Pinto, William C Keel, Anton M Koekemoer, Sandor Kruk, Karen L Masters, Oscar Montoya C., Mason Redden, Matthew R Thorne, Emily R Walls, Deneth Weerasinghe and John R WeaverMonthly Notices of the Royal Astronomical Society 539 (4) 2967 (2025)
https://doi.org/10.1093/mnras/staf541
Astronomical Image Superresolution Reconstruction with Deep Learning for Better Identification of Interacting Galaxies
Jiawei Miao, Liangping Tu, Hao Liu and Jian ZhaoThe Astrophysical Journal Supplement Series 278 (2) 35 (2025)
https://doi.org/10.3847/1538-4365/adca34
Measuring the Intracluster Light Fraction with Machine Learning
Louisa Canepa, Sarah Brough, Francois Lanusse, Mireia Montes and Nina HatchThe Astrophysical Journal 980 (2) 245 (2025)
https://doi.org/10.3847/1538-4357/adabc7
Galaxy merger challenge: A comparison study between machine learning-based detection methods
B. Margalef-Bentabol, L. Wang, A. La Marca, C. Blanco-Prieto, D. Chudy, H. Domínguez-Sánchez, A. D. Goulding, A. Guzmán-Ortega, M. Huertas-Company, G. Martin, W. J. Pearson, V. Rodriguez-Gomez, M. Walmsley, R. W. Bickley, C. Bottrell, C. Conselice and D. O’RyanAstronomy & Astrophysics 687 A24 (2024)
https://doi.org/10.1051/0004-6361/202348239
The limitations (and potential) of non-parametric morphology statistics for post-merger identification
Scott Wilkinson, Sara L Ellison, Connor Bottrell, Robert W Bickley, Shoshannah Byrne-Mamahit, Leonardo Ferreira and David R PattonMonthly Notices of the Royal Astronomical Society 528 (4) 5558 (2024)
https://doi.org/10.1093/mnras/stae287
33 (2024)
https://doi.org/10.1007/978-981-97-8735-7_3
ERGO-ML: comparing IllustrisTNG and HSC galaxy images via contrastive learning
Lukas Eisert, Connor Bottrell, Annalisa Pillepich, Rhythm Shimakawa, Vicente Rodriguez-Gomez, Dylan Nelson, Eirini Angeloudi and Marc Huertas-CompanyMonthly Notices of the Royal Astronomical Society 528 (4) 7411 (2024)
https://doi.org/10.1093/mnras/stae481
Do galaxy mergers prefer under-dense environments?
U. Sureshkumar, A. Durkalec, A. Pollo, W. J. Pearson, D. J. Farrow, A. Narayanan, J. Loveday, E. N. Taylor and L. E. SuelvesAstronomy & Astrophysics 686 A40 (2024)
https://doi.org/10.1051/0004-6361/202347705
Characterizing tidal features around galaxies in cosmological simulations
A Khalid, S Brough, G Martin, L C Kimmig, C D P Lagos, R -S Remus and C Martinez-LombillaMonthly Notices of the Royal Astronomical Society 530 (4) 4422 (2024)
https://doi.org/10.1093/mnras/stae1064
The effect of image quality on galaxy merger identification with deep learning
Robert W Bickley, Scott Wilkinson, Leonardo Ferreira, Sara L Ellison, Connor Bottrell and Debarpita JyotiMonthly Notices of the Royal Astronomical Society 534 (3) 2533 (2024)
https://doi.org/10.1093/mnras/stae2246
A post-merger enhancement only in star-forming Type 2 Seyfert galaxies: the deep learning view
M S Avirett-Mackenzie, C Villforth, M Huertas-Company, S Wuyts, D M Alexander, S Bonoli, A Lapi, I E Lopez, C Ramos Almeida and F ShankarMonthly Notices of the Royal Astronomical Society 528 (4) 6915 (2024)
https://doi.org/10.1093/mnras/stae183
Detecting galaxy tidal features using self-supervised representation learning
Alice Desmons, Sarah Brough and Francois LanusseMonthly Notices of the Royal Astronomical Society 531 (4) 4070 (2024)
https://doi.org/10.1093/mnras/stae1402
Automating galaxy morphology classification using k-nearest neighbours and non-parametric statistics
Kavya Mukundan, Preethi Nair, Jeremy Bailin and Wenhao LiMonthly Notices of the Royal Astronomical Society 533 (1) 292 (2024)
https://doi.org/10.1093/mnras/stae1684
Galaxy mergers in UNIONS – I. A simulation-driven hybrid deep learning ensemble for pure galaxy merger classification
Leonardo Ferreira, Robert W Bickley, Sara L Ellison, David R Patton, Shoshannah Byrne-Mamahit, Scott Wilkinson, Connor Bottrell, Sébastien Fabbro, Stephen D J Gwyn and Alan McConnachieMonthly Notices of the Royal Astronomical Society 533 (3) 2547 (2024)
https://doi.org/10.1093/mnras/stae1885
Identifying Mergers in the Legacy Surveys with Few-shot Learning
Shoulin Wei, Xiang Song, Zhijian Zhang, Bo Liang, Wei Dai, Wei Lu and Junxi TaoThe Astrophysical Journal Supplement Series 274 (2) 23 (2024)
https://doi.org/10.3847/1538-4365/ad66ca
Uncovering tidal treasures: automated classification of faint tidal features in DECaLS data
Alexander J Gordon, Annette M N Ferguson and Robert G MannMonthly Notices of the Royal Astronomical Society 534 (2) 1459 (2024)
https://doi.org/10.1093/mnras/stae2169
CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, et al.The Astrophysical Journal Letters 976 (1) L8 (2024)
https://doi.org/10.3847/2041-8213/ad8dd4
Accurately Estimating Redshifts from CSST Slitless Spectroscopic Survey Using Deep Learning
Xingchen Zhou, Yan Gong, Xin Zhang, Nan Li, Xian-Min Meng, Xuelei Chen, Run Wen, Yunkun Han, Hu Zou, Xian Zhong Zheng, Xiaohu Yang, Hong Guo and Pengjie ZhangThe Astrophysical Journal 977 (1) 69 (2024)
https://doi.org/10.3847/1538-4357/ad8bbf
1 (2024)
https://doi.org/10.1007/978-981-97-8735-7_1
Identifying Galaxy Mergers in Simulated CEERS NIRCam Images Using Random Forests
Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Vicente Rodriguez-Gomez, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Antonello Calabró, Nikko J. Cleri, M. C. Cooper, Luca Costantin, Darren Croton, Mark Dickinson, Steven L. Finkelstein, Boris Häußler, Benne W. Holwerda, Anton M. Koekemoer, Peter Kurczynski, Ray A. Lucas, Kameswara Bharadwaj Mantha, Casey Papovich, Pablo G. Pérez-González, Nor Pirzkal, Rachel S. Somerville, Amber N. Straughn and Sandro TacchellaThe Astrophysical Journal 942 (1) 54 (2023)
https://doi.org/10.3847/1538-4357/ac9f10
Galaxy and mass assembly (GAMA): comparing visually and spectroscopically identified galaxy merger samples
Alice Desmons, Sarah Brough, Cristina Martínez-Lombilla, Roberto De Propris, Benne Holwerda and Ángel R López-SánchezMonthly Notices of the Royal Astronomical Society 523 (3) 4381 (2023)
https://doi.org/10.1093/mnras/stad1639
AGNs in post-mergers from the ultraviolet near infrared optical northern survey
Robert W Bickley, Sara L Ellison, David R Patton and Scott WilkinsonMonthly Notices of the Royal Astronomical Society 519 (4) 6149 (2023)
https://doi.org/10.1093/mnras/stad088
Galaxy pairs in The Three Hundred simulations II: studying bound ones and identifying them via machine learning
Ana Contreras-Santos, Alexander Knebe, Weiguang Cui, et al.Monthly Notices of the Royal Astronomical Society 522 (1) 1270 (2023)
https://doi.org/10.1093/mnras/stad1061
ERGO-ML: towards a robust machine learning model for inferring the fraction of accreted stars in galaxies from integral-field spectroscopic maps
Eirini Angeloudi, Jesús Falcón-Barroso, Marc Huertas-Company, Regina Sarmiento, Annalisa Pillepich, Daniel Walo-Martín and Lukas EisertMonthly Notices of the Royal Astronomical Society 523 (4) 5408 (2023)
https://doi.org/10.1093/mnras/stad1669
The Dawes Review 10: The impact of deep learning for the analysis of galaxy surveys
M. Huertas-Company and F. LanussePublications of the Astronomical Society of Australia 40 (2023)
https://doi.org/10.1017/pasa.2022.55
Merger identification through photometric bands, colours, and their errors
L. E. Suelves, W. J. Pearson and A. PolloAstronomy & Astrophysics 669 A141 (2023)
https://doi.org/10.1051/0004-6361/202244509
Astrophysics with the Laser Interferometer Space Antenna
Pau Amaro-Seoane, Jeff Andrews, Manuel Arca Sedda, Abbas Askar, Quentin Baghi, Razvan Balasov, Imre Bartos, Simone S. Bavera, Jillian Bellovary, Christopher P. L. Berry, Emanuele Berti, Stefano Bianchi, Laura Blecha, Stéphane Blondin, Tamara Bogdanović, Samuel Boissier, Matteo Bonetti, Silvia Bonoli, Elisa Bortolas, Katelyn Breivik, Pedro R. Capelo, Laurentiu Caramete, Federico Cattorini, Maria Charisi, Sylvain Chaty, et al.Living Reviews in Relativity 26 (1) (2023)
https://doi.org/10.1007/s41114-022-00041-y
Hidden depths in the local Universe: The Stellar Stream Legacy Survey
David Martínez-Delgado, Andrew P. Cooper, Javier Román, et al.Astronomy & Astrophysics 671 A141 (2023)
https://doi.org/10.1051/0004-6361/202245011
Galaxy mergers in Subaru HSC-SSP: A deep representation learning approach for identification, and the role of environment on merger incidence
Kiyoaki Christopher Omori, Connor Bottrell, Mike Walmsley, Hassen M. Yesuf, Andy D. Goulding, Xuheng Ding, Gergö Popping, John D. Silverman, Tsutomu T. Takeuchi and Yoshiki TobaAstronomy & Astrophysics 679 A142 (2023)
https://doi.org/10.1051/0004-6361/202346743
3D detection and characterization of ALMA sources through deep learning
Michele Delli Veneri, Łukasz Tychoniec, Fabrizia Guglielmetti, Giuseppe Longo and Eric VillardMonthly Notices of the Royal Astronomical Society 518 (3) 3407 (2022)
https://doi.org/10.1093/mnras/stac3314
SDSS-IV MaNGA: Unveiling Galaxy Interaction by Merger Stages with Machine Learning
Yu-Yen Chang, Lihwai Lin, Hsi-An Pan, Chieh-An Lin, Bau-Ching Hsieh, Connor Bottrell and Pin-Wei WangThe Astrophysical Journal 937 (2) 97 (2022)
https://doi.org/10.3847/1538-4357/ac8c27
A Simulation-driven Deep Learning Approach for Separating Mergers and Star-forming Galaxies: The Formation Histories of Clumpy Galaxies in All of the CANDELS Fields
Leonardo Ferreira, Christopher J. Conselice, Ulrike Kuchner and Clár-Bríd TohillThe Astrophysical Journal 931 (1) 34 (2022)
https://doi.org/10.3847/1538-4357/ac66ea
The merger fraction of post-starburst galaxies in UNIONS
Scott Wilkinson, Sara L Ellison, Connor Bottrell, Robert W Bickley, Stephen Gwyn, Jean-Charles Cuillandre and Vivienne WildMonthly Notices of the Royal Astronomical Society 516 (3) 4354 (2022)
https://doi.org/10.1093/mnras/stac1962
North Ecliptic Pole merging galaxy catalogue
W. J. Pearson, L. E. Suelves, S. C.-C. Ho, et al.Astronomy & Astrophysics 661 A52 (2022)
https://doi.org/10.1051/0004-6361/202141013
Characterization of low surface brightness structures in annotated deep images
Elisabeth Sola, Pierre-Alain Duc, Felix Richards, et al.Astronomy & Astrophysics 662 A124 (2022)
https://doi.org/10.1051/0004-6361/202142675
Large-Scale Structure of the Universe
Kana MoriwakiSpringer Theses, Large-Scale Structure of the Universe 1 (2022)
https://doi.org/10.1007/978-981-19-5880-9_1
Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02
I. B. VAVILOVA, V. KHRAMTSOV, D. V. DOBRYCHEVA, et al.
Kosmìčna nauka ì tehnologìâ 28 (1) 03 (2022)
https://doi.org/10.15407/knit2022.01.003
Kosmìčna nauka ì tehnologìâ 28 (1) 03 (2022)
https://doi.org/10.15407/knit2022.01.003
Star formation characteristics of CNN-identified post-mergers in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)
Robert W Bickley, Sara L Ellison, David R Patton, et al.Monthly Notices of the Royal Astronomical Society 514 (3) 3294 (2022)
https://doi.org/10.1093/mnras/stac1500
The combined and respective roles of imaging and stellar kinematics in identifying galaxy merger remnants
Connor Bottrell, Maan H Hani, Hossen Teimoorinia, David R Patton and Sara L EllisonMonthly Notices of the Royal Astronomical Society 511 (1) 100 (2022)
https://doi.org/10.1093/mnras/stab3717
A new automated tool for the spectral classification of OB stars
E. Kyritsis, G. Maravelias, A. Zezas, et al.Astronomy & Astrophysics 657 A62 (2022)
https://doi.org/10.1051/0004-6361/202040224
DECORAS: detection and characterization of radio-astronomical sources using deep learning
S Rezaei, J P McKean, M Biehl and A JavadpourMonthly Notices of the Royal Astronomical Society 510 (4) 5891 (2022)
https://doi.org/10.1093/mnras/stab3519
Machine learning technique for morphological classification of galaxies from the SDSS. III. The CNN image-based inference of detailed features
V. KHRAMTSOV, I. B. VAVILOVA, D. V. DOBRYCHEVA, et al.Kosmìčna nauka ì tehnologìâ 28 (5) 27 (2022)
https://doi.org/10.15407/knit2022.05.027
Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG
Robert W Bickley, Connor Bottrell, Maan H Hani, et al.Monthly Notices of the Royal Astronomical Society 504 (1) 372 (2021)
https://doi.org/10.1093/mnras/stab806
DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains
A Ćiprijanović, D Kafkes, K Downey, et al.Monthly Notices of the Royal Astronomical Society 506 (1) 677 (2021)
https://doi.org/10.1093/mnras/stab1677
Towards robust determination of non-parametric morphologies in marginal astronomical data: resolving uncertainties with cosmological hydrodynamical simulations
Mallory D Thorp, Asa F L Bluck, Sara L Ellison, et al.Monthly Notices of the Royal Astronomical Society 507 (1) 886 (2021)
https://doi.org/10.1093/mnras/stab2201
Merger or Not: Accounting for Human Biases in Identifying Galactic Merger Signatures
Erini L. Lambrides, Duncan J. Watts, Marco Chiaberge, Kirill Tchernyshyov, Allison Kirkpatrick, Eileen T. Meyer, Timothy Heckman, Raymond Simons, Oz Amram, Kirsten R. Hall, Arianna Long and Colin NormanThe Astrophysical Journal 919 (1) 43 (2021)
https://doi.org/10.3847/1538-4357/ac0fdf
Galaxy morphology classification using automated machine learning
Moonzarin RezaAstronomy and Computing 37 100492 (2021)
https://doi.org/10.1016/j.ascom.2021.100492
An IFU View of the Active Galactic Nuclei in MaNGA Galaxy Pairs
Gaoxiang Jin, Y. Sophia Dai, Hsi-An Pan, Lihwai Lin, Cheng Li, Bau-Ching Hsieh, Shiyin Shen, Fang-Ting Yuan, Shuai Feng, Cheng Cheng, Hai Xu, Jia-Sheng Huang and Kai ZhangThe Astrophysical Journal 923 (1) 6 (2021)
https://doi.org/10.3847/1538-4357/ac2901
Galaxy interactions in IllustrisTNG-100, I: The power and limitations of visual identification
Kelly A Blumenthal, Jorge Moreno, Joshua E Barnes, et al.Monthly Notices of the Royal Astronomical Society 492 (2) 2075 (2020)
https://doi.org/10.1093/mnras/stz3472
Towards a consistent framework of comparing galaxy mergers in observations and simulations
L. Wang, W. J. Pearson and V. Rodriguez-GomezAstronomy & Astrophysics 644 A87 (2020)
https://doi.org/10.1051/0004-6361/202038084
Galaxy Merger Rates up to z ∼ 3 Using a Bayesian Deep Learning Model: A Major-merger Classifier Using IllustrisTNG Simulation Data
Leonardo Ferreira, Christopher J. Conselice, Kenneth Duncan, Ting-Yun Cheng, Alex Griffiths and Amy WhitneyThe Astrophysical Journal 895 (2) 115 (2020)
https://doi.org/10.3847/1538-4357/ab8f9b
Interacting galaxies in the IllustrisTNG simulations - I: Triggered star formation in a cosmological context
David R Patton, Kieran D Wilson, Colin J Metrow, et al.Monthly Notices of the Royal Astronomical Society 494 (4) 4969 (2020)
https://doi.org/10.1093/mnras/staa913
DeepMerge: Classifying high-redshift merging galaxies with deep neural networks
A. Ćiprijanović, G.F. Snyder, B. Nord and J.E.G. PeekAstronomy and Computing 32 100390 (2020)
https://doi.org/10.1016/j.ascom.2020.100390
Galaxy pairs in the Sloan Digital Sky Survey – XIV. Galaxy mergers do not lie on the fundamental metallicity relation
Martin Sparre, David R Patton, Sara L Ellison and Sebastián BustamanteMonthly Notices of the Royal Astronomical Society 494 (3) 3469 (2020)
https://doi.org/10.1093/mnras/staa1025
Mergers trigger active galactic nuclei out to z ∼ 0.6
F. Gao, L. Wang, W. J. Pearson, et al.Astronomy & Astrophysics 637 A94 (2020)
https://doi.org/10.1051/0004-6361/201937178
Census and classification of low-surface-brightness structures in nearby early-type galaxies from the MATLAS survey
Michal Bílek, Pierre-Alain Duc, Jean-Charles Cuillandre, et al.Monthly Notices of the Royal Astronomical Society 498 (2) 2138 (2020)
https://doi.org/10.1093/mnras/staa2248
Effect of galaxy mergers on star-formation rates
W. J. Pearson, L. Wang, M. Alpaslan, et al.Astronomy & Astrophysics 631 A51 (2019)
https://doi.org/10.1051/0004-6361/201936337
Deep learning predictions of galaxy merger stage and the importance of observational realism
Connor Bottrell, Maan H Hani, Hossen Teimoorinia, et al.Monthly Notices of the Royal Astronomical Society 490 (4) 5390 (2019)
https://doi.org/10.1093/mnras/stz2934
Narrow-band Hα imaging of nearby Wolf–Rayet galaxies
A Paswan, Kanak Saha and A OmarMonthly Notices of the Royal Astronomical Society 490 (3) 3448 (2019)
https://doi.org/10.1093/mnras/stz2833