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A software package able to simulate imaging observations of galaxy clusters by the Chandra X-ray telescope is here presented. We start from high resolution N-body hydrodynamical simulations of galaxy clusters and assign to each gas particle…

Astrophysics · Physics 2007-05-23 A. Gardini

The next generation of submillimetre/millimetre instruments will provide us with a deeper insight into the mechanisms that rule galaxy formation. As the brightest starbursts are thought to be heavily obscured at optical wavelengths, the…

Astrophysics · Physics 2007-05-23 A. -L. Melchior , F. Combes , B. Guiderdoni , S. Hatton

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful…

We estimate the distribution of intrinsic shapes of the APM galaxy clusters from their corresponding distribution of projected shapes. We smooth the discrete galaxy distribution and define the cluster shape by fitting the best ellipse to…

Astrophysics · Physics 2007-05-23 Spyros Basilakos , Manolis Plionis , Steve Maddox

The new generation of deep photometric surveys requires unprecedentedly precise shape and photometry measurements of billions of galaxies to achieve their main science goals. At such depths, one major limiting factor is the blending of…

We present high-resolution mass reconstructions for five massive cluster-lenses spanning a redshift range from $z = 0.18$--0.57 utilising archival {\it Hubble Space Telescope} ({\it HST}) data and applying galaxy-galaxy lensing techniques.…

Astrophysics · Physics 2008-11-26 Priyamvada Natarajan , Gabriella De Lucia , Volker Springel

Upcoming large astronomical surveys are expected to capture an unprecedented number of strong gravitational lensing systems. Deep learning is emerging as a promising practical tool for the detection and quantification of these galaxy-scale…

Gravitational lensing has now become a popular tool to measure the mass distribution of structures in the Universe on various scales. Here we focus on the study of galaxy's scale dark matter halos with galaxy-galaxy lensing techniques:…

Astrophysics · Physics 2007-05-23 M. Limousin , J-P. Kneib , P. Natarajan

One of the primary limiting sources of systematic uncertainty in forthcoming weak lensing measurements is systematic uncertainty in the quantitative relationship between the distortions due to gravitational lensing and the measurable…

Cosmology and Nongalactic Astrophysics · Physics 2017-02-10 Eric Huff , Rachel Mandelbaum

The arrival times, positions, and fluxes of multiple images in strong lens systems can be used to infer the presence of dark subhalos in the deflector, and thus test predictions of cold dark matter models. However, gravitational lensing…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-16 Daniel Gilman , Adriano Agnello , Tommaso Treu , Charles R. Keeton , Anna M. Nierenberg

The galaxy luminosity function and galaxy stellar mass function are fundamental statistics in the testing of galaxy formation models. Theoretical predictions based on cosmological simulations can deviate from observations, especially at the…

Cosmology and Nongalactic Astrophysics · Physics 2021-10-18 Lin Tang , Weipeng Lin , Yang Wang , N. R. Napolitano

The formation of Hoag-type galaxies with central spheroidal galaxies and outer stellar rings has yet to be understood in astronomy. We consider that these unique objects were formed from the past interaction between elliptical galaxies and…

Instrumentation and Methods for Astrophysics · Physics 2019-04-08 Eleanor Leung , Kenji Bekki , Lyndon While

Strong gravitational lensing provides a powerful tool to directly infer the dark matter (DM) subhalo mass function (SHMF) in lens galaxies. However, comparing observationally inferred SHMFs to theoretical predictions remains challenging, as…

We show that a Denoising Diffusion Probabalistic Model (DDPM), a class of score-based generative model, can be used to produce realistic mock images that mimic observations of galaxies. Our method is tested with Dark Energy Spectroscopic…

Instrumentation and Methods for Astrophysics · Physics 2022-02-01 Michael J. Smith , James E. Geach , Ryan A. Jackson , Nikhil Arora , Connor Stone , Stéphane Courteau

Sky models used in radio interferometric data processing primarily consist of compact and discrete radio sources. When there is a need to model large scale diffuse structure such as the Galaxy, specialized source models are sought after for…

Instrumentation and Methods for Astrophysics · Physics 2024-12-04 Sarod Yatawatta

We analyze the optical morphologies of galaxies in the IllustrisTNG simulation at $z\sim0$ with a Convolutional Neural Network trained on visual morphologies in the Sloan Digital Sky Survey. We generate mock SDSS images of a mass complete…

Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between dark matter density fields…

Cosmology and Nongalactic Astrophysics · Physics 2024-03-19 Victoria Ono , Core Francisco Park , Nayantara Mudur , Yueying Ni , Carolina Cuesta-Lazaro , Francisco Villaescusa-Navarro

The optical morphology of galaxies is strongly related to galactic environment, with the fraction of early-type galaxies increasing with local galaxy density. In this work we present the first analysis of the galaxy morphology-density…

While clusters of galaxies are considered one of the most important cosmological probes, the standard spherical modelling of the dark matter and the intracluster medium is only a rough approximation. Indeed, it is well established both…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-11 Marceau Limousin , Andrea Morandi , Mauro Sereno , Massimo Meneghetti , Stefano Ettori , Matthias Bartelmann , Tomas Verdugo

We propose a new method to estimate the photometric redshift of galaxies by using the full galaxy image in each measured band. This method draws from the latest techniques and advances in machine learning, in particular Deep Neural…

Instrumentation and Methods for Astrophysics · Physics 2016-06-16 Ben Hoyle
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