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Related papers: Astronomical imaging: The theory of everything

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Observational astronomy has changed drastically in the last decade: manually driven target-by-target instruments have been replaced by fully automated robotic telescopes. Data acquisition methods have advanced to the point that terabytes of…

Astronomy has a distinguished tradition of using technology to accelerate the quality and effectiveness of science, and data-intensive initiatives such as the Virtual Observatory lead the way amongst other fields of science. However,…

Astrophysics · Physics 2007-05-23 Ray P Norris

The study of the morphology of galaxies is important in order to understand the formation and evolution of galaxies and their sub-components as a function of luminosity, environment, and star-formation and galaxy assembly over cosmic time.…

Cosmology and Nongalactic Astrophysics · Physics 2012-01-12 Yogesh Wadadekar

Galaxy models are fundamental to exploiting surveys of our Galaxy. There is now a significant body of work on axisymmetric models. A model can be defined by giving the DF of each major class of stars and of dark matter. Then the…

Astrophysics of Galaxies · Physics 2018-06-13 James Binney

Astronomy, as many other scientific disciplines, is facing a true data deluge which is bound to change both the praxis and the methodology of every day research work. The emerging field of astroinformatics, while on the one end appears…

Instrumentation and Methods for Astrophysics · Physics 2015-06-03 Massimo Brescia , Giuseppe Longo

The prevalence of AI-generated imagery has raised concerns about the authenticity of astronomical images, especially with advanced text-to-image models like Stable Diffusion producing highly realistic synthetic samples. Existing detection…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Mohammed Talha Alam , Raza Imam , Mohsen Guizani , Fakhri Karray

In Astronomy, a huge amount of image data is generated daily by photometric surveys, which scan the sky to collect data from stars, galaxies and other celestial objects. In this paper, we propose a technique to leverage unlabeled…

Computer Vision and Pattern Recognition · Computer Science 2020-06-26 Ana Martinazzo , Mateus Espadoto , Nina S. T. Hirata

In this work, we provide an efficient and realistic data-driven approach to simulate astronomical images using deep generative models from machine learning. Our solution is based on a variant of the generative adversarial network (GAN) with…

Machine Learning · Computer Science 2019-09-27 Mohamad Dia , Elodie Savary , Martin Melchior , Frederic Courbin

Cosmology is undergoing an explosive period of activity, fueled both by new, accurate astrophysical data and by innovative theoretical developments. Cosmological parameters such as the total density of the Universe and the rate of…

Astrophysics · Physics 2007-05-23 A. S. Sakharov , H. Hofer

Galactic all-sky maps at very disparate frequencies, like in the radio and $\gamma$-ray regime, show similar morphological structures. This mutual information reflects the imprint of the various physical components of the interstellar…

The last decade has seen tremendous progress in our ability to generate realistic-looking data, be it images, text, audio, or video. Here, we discuss the closely related problem of quantifying realism, that is, designing functions that can…

Machine Learning · Computer Science 2024-05-22 Lucas Theis

The combination of huge databases of galaxy spectra and advances in evolutionary synthesis models in the past few years has renewed interest in an old question: How to estimate the star formation history of a galaxy out of its integrated…

Astrophysics · Physics 2009-11-13 Roberto Cid Fernandes

Any realistic theory of galaxy formation must be set in the context of a model for the formation of structure in the universe. We describe a powerful approach -- semi-analytic modelling -- that combines a set of simple rules describing the…

Astrophysics · Physics 2007-05-23 C. M. Baugh , S. Cole , C. S. Frenk , A. J. Benson , C. G. Lacey

It is well known that the best way to understand astronomical data is through machine learning, where a "black box" is set up, inside which a kind of artificial intelligence learns how to interpret the features in the data. We suggest that…

Instrumentation and Methods for Astrophysics · Physics 2024-04-01 Douglas Scott , Ali Frolop

The cosmological exploitation of modern photometric galaxy surveys requires both accurate (unbiased) and precise (narrow) redshift probability distributions derived from broadband photometry. Existing methodologies do not meet those…

Cosmology and Nongalactic Astrophysics · Physics 2019-08-21 Boris Leistedt , David W. Hogg , Risa H. Wechsler , Joe DeRose

Space exploration has always been a source of inspiration for humankind, and thanks to modern telescopes, it is now possible to observe celestial bodies far away from us. With a growing number of real and imaginary images of space available…

Computer Vision and Pattern Recognition · Computer Science 2021-11-24 Davide Coccomini , Nicola Messina , Claudio Gennaro , Fabrizio Falchi

This study investigates the application of generative artificial intelligence in architectural design. We present a novel methodology that combines multiple neural networks to create an unsupervised and unmoderated stream of unique…

Artificial Intelligence · Computer Science 2024-07-15 Alexey Tikhonov , Dmitry Sinyavin

Since the early 1970s, stellar population modelling has been one of the basic tools for understanding the physics of unresolved systems from observation of their integrated light. Models allow us to relate the integrated spectra (or…

Instrumentation and Methods for Astrophysics · Physics 2013-12-03 Miguel Cerviño

It is argued that the astronomy of the twenty-first century will be dominated by computer-based manipulation of huge homogeneous surveys of various types of astronomical objects. Furthermore combination of all observations with large…

Astrophysics · Physics 2009-10-31 Sidney van den Bergh

The Hubble tuning fork diagram, based on morphology and established in the 1930s, has always been the preferred scheme for classification of galaxies. However, the current large amount of multiwavelength data, most often spectra, for…

Cosmology and Nongalactic Astrophysics · Physics 2009-09-24 Didier Fraix-Burnet
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