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Fine-grained estimation of galaxy merger stages from observations is a key problem useful for validation of our current theoretical understanding of galaxy formation.
On the gravitational stability of a disk of stars
A. Toomre · 1964
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Cosmological hydrodynamics with adaptive mesh refinement. A new high resolution code called RAMSES
R. Teyssier · 2002
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Stellar population synthesis at the resolution of 2003
G. Bruzual and S. Charlot · 2003
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Galactic Stellar and Substellar Initial Mass Function
Gilles Chabrier · 2003
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The origin and implications of dark matter anisotropic cosmic infall on L ∗ L_{*} haloes
D. Aubert, C. Pichon, and S. Colombi · 2004
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Towards an accurate model for the Antennae galaxies
S. J. Karl, T. Naab, P. H. Johansson, Ch. Theis, and C. M. Boily · 2008
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Galaxy merger morphologies and time-scales from simulations of equal-mass gas-rich disc mergers
Jennifer M. Lotz, Patrik Jonsson, T. J. Cox, and Joel R. Primack · 2008
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Building merger trees from cosmological N-body simulations. Towards improving galaxy formation models using subhaloes
D. Tweed, J. Devriendt, J. Blaizot, S. Colombi, and A. Slyz · 2009
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Candels: the cosmic assembly near-infrared deep extragalactic legacy survey
Norman A Grogin, Dale D Kocevski, SM Faber, Henry C Ferguson, Anton M Koekemoer, Adam G Riess, Viviana Acquaviva, David M Alexander, Omar Almaini, Matthew LN Ashby, et al · 2011
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The major and minor galaxy merger rates at z< 1.5
Jennifer M Lotz, Patrik Jonsson, TJ Cox, Darren Croton, Joel R Primack, Rachel S Somerville, and Kyle Stewart · 2011
Cited alongside, same era.
The Structures and Total (Minor + Major) Merger Histories of Massive Galaxies up to z ~
Asa F. L. Bluck, Christopher J. Conselice, Fernand o Buitrago, Ruth Grützbauch, Carlos Hoyos, Alice Mortlock, and Amanda E. Bauer · 2012
Cited alongside, same era.
The Cosmological Size and Velocity Dispersion Evolution of Massive Early-type Galaxies
Ludwig Oser, Thorsten Naab, Jeremiah P. Ostriker, and Peter H. Johansson · 2012
Cited alongside, same era.
On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton · 2013
Cited alongside, same era.
Dancing in the dark: galactic properties trace spin swings along the cosmic web
Y. Dubois, C. Pichon, C. Welker, D. Le Borgne, J. Devriendt, C. Laigle, S. Codis, D. Pogosyan, S. Arnouts, K. Benabed, E. Bertin, J. Blaizot, F. Bouchet, J. F. Cardoso, S. Colombi, V. de Lapparent, V. Desjacques, R. Gavazzi, S. Kassin, T. Kimm, H. McCracken, B. Milliard, S. Peirani, S. Prunet, S. Rouberol, J. Silk, A. Slyz, T. Sousbie, R. Teyssier, L. Tresse, M. Treyer, D. Vibert, and M. Volonteri · 2014
Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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The fate of the Antennae galaxies
Natalia Lahén, Peter H. Johansson, Antti Rantala, Thorsten Naab, and Matteo Frigo · 2018
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Observational Constraints on the Merger History of Galaxies since z ≈ \approx 6: Probabilistic Galaxy Pair Counts in the CANDELS Fields
Kenneth Duncan, Christopher J. Conselice, Carl Mundy, Eric Bell, Jennifer Donley, Audrey Galametz, Yicheng Guo, Norman A. Grogin, Nimish Hathi, Jeyhan Kartaltepe, Dale Kocevski, Anton M. Koekemoer, Pablo G. Pérez-González, Kameswara B. Mantha, Gregory F. Snyder, and Mauro Stefanon · 2019
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Horizon-AGN virtual observatory - 1. SED-fitting performance and forecasts for future imaging surveys
C. Laigle, I. Davidzon, O. Ilbert, J. Devriendt, D. Kashino, C. Pichon, P. Capak, S. Arnouts, S. de la Torre, Y. Dubois, G. Gozaliasl, D. Le Borgne, S. Lilly, H. J. McCracken, M. Salvato, and A. Slyz · 2019
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Identifying galaxy mergers in observations and simulations with deep learning
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Cited alongside, same era.
The merger rate of galaxies in the Illustris simulation: a comparison with observations and semi-empirical models
Vicente Rodriguez-Gomez, Shy Genel, Mark Vogelsberger, Debora Sijacki, Annalisa Pillepich, Laura V. Sales, Paul Torrey, Greg Snyder, Dylan Nelson, Volker Springel, Chung-Pei Ma, and Lars Hernquist · 2015
Cited alongside, same era.
Compaction and quenching of high-z galaxies in cosmological simulations: blue and red nuggets
Adi Zolotov, Avishai Dekel, Nir Mandelker, Dylan Tweed, Shigeki Inoue, Colin DeGraf, Daniel Ceverino, Joel R. Primack, Guillermo Barro, and Sandra M. Faber · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
The Horizon-AGN simulation: evolution of galaxy properties over cosmic time
S. Kaviraj, C. Laigle, T. Kimm, J. E. G. Devriendt, Y. Dubois, C. Pichon, A. Slyz, E. Chisari, and S. Peirani · 2017
Cited alongside, same era.
WJ Pearson, L Wang, JW Trayford, CE Petrillo, and FFS van der Tak · 2019
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Machine learning from cosmological simulations to identify distant galaxy mergers
Gregory Snyder · 2019
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Automated distant galaxy merger classifications from Space Telescope images using the Illustris simulation
Gregory F. Snyder, Vicente Rodriguez-Gomez, Jennifer M. Lotz, Paul Torrey, Amanda C. N. Quirk, Lars Hernquist, Mark Vogelsberger, and Peter E. Freeman · 2019
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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 Whitney · 2020
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Test-time training with self-supervision for generalization under distribution shifts
Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A Efros, and Moritz Hardt · 2020
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