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Intelligent Astrophysics

Part of the Emergence, Complexity and Computation Book Series (volume 39)

Editors: Zelinka, Ivan; Brescia, Massimo; Baron, Dalya

DOI: 10.1007/978-3-030-65867-0

ISBN: 978-3-030-65866-3

Publisher: Springer International Publishing - Springer Journals

Apr 16, 2021

1 - 10 of 12 Chapters

Available

Artificial Intelligence in Astrophysics

Zelinka, Ivan; Cong Truong, Thanh; Quoc Bao, Diep; Kojecky, Lumir; Amer, Eslam

Pages: 1 –28

[Artificial intelligence and its subparts (like evolutionary algorithms, machine learning,…\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek}...
Available

The Complexity and Information Content of Simulated Universes

Vazza, Franco

Pages: 29 –56

[The emergence of a complex, large-scale organisation of cosmic matter into the Cosmic Web well exemplifies of how complexity can be produced by simple initial conditions and simple physical laws. Connecting the stunning variety of multi-messenger observations to the complex interplay of...
Available

The Voronoi Tessellation Method in Astronomy

Vavilova, Iryna; Elyiv, Andrii; Dobrycheva, Daria; Melnyk, Olga

Pages: 57 –79

[The Voronoi tessellation is a natural way of space segmentation, which has many applications in various fields of science and technology as well as in social sciences and visual art. The varieties of the Voronoi tessellation methods are commonly used in computational fluid dynamics,...
Available

Statistical Characterization and Classification of Astronomical Transients with Machine Learning in the era of the Vera C. Rubin Observatory

Vicedomini, Marco; Brescia, Massimo; Cavuoti, Stefano; Riccio, Giuseppe; Longo, Giuseppe

Pages: 81 –113

[Astronomy has entered the multi-messenger data era and Machine Learning has found widespread use in a large variety of applications. The exploitation of synoptic (multi-band and multi-epoch) surveys, like LSST (Legacy Survey of Space and Time), requires an extensive use of automatic methods for...
Available

Application of Machine and Deep Learning Methods to the Analysis of IACTs Data

Bruno, Alessandro; Pagliaro, Antonio; La Parola, Valentina

Pages: 115 –136

[The Imaging Atmospheric Cherenkov technique opened a previously inaccessible window for the study of astrophysical sources of radiation in the very high-energy regime (TeV) and is playing a significant role in the discovery and characterization of very high-energy gamma-ray emitters. However,...
Available

Intelligent Photometric Identification of Extragalactic Objects from AllWISE×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document}Pan-STARRS DR1 Data

Khramtsov, Vladislav; Akhmetov, Volodymyr; Fedorov, Peter; Khlamov, Sergii; Dmytrenko, Artem; Velichko, Anna

Pages: 137 –152

[We present the results of identification of extragalactic objects within cross-matching result of the two photometric catalogues, AllWISE and Pan-STARRS DR1. To separate galaxies and quasars from stars, we constructed a machine learning model, trained on photometric information from optical and...
Available

Ensemble Classifiers for Pulsar Detection

Holewik, Jakub; Schaefer, Gerald

Pages: 153 –166

[A common way of identifying pulsars is based on their emitted radio waves. To allow for automated screening of a large number of radio signals, machine learning methods can be adopted. One challenge here though is that training such methods is hampered by the inherent imbalance in the available...
Available

Periodic Astrometric Signal Recovery Through Convolutional Autoencoders

Veneri, Michele Delli; Desdoigts, Louis; Schmitz, Morgan A.; Krone-Martins, Alberto; Ishida, Emille E. O.; Tuthill, Peter; de Souza, Rafael S.; Scalzo, Richard; Brescia, Massimo; Longo, Giuseppe; Picariello, Antonio

Pages: 167 –195

[Astrometric detection involves precise measurements of stellar positions, and it is widely regarded as the leading concept presently ready to find Earth-mass planets in temperate orbits around nearby sun-like stars. The TOLIMAN space telescope [39] is a low-cost, agile mission concept dedicated...
Available

Comparison of Outlier Detection Methods on Astronomical Image Data

Doorenbos, Lars; Cavuoti, Stefano; Brescia, Massimo; D’Isanto, Antonio; Longo, Giuseppe

Pages: 197 –223

[Among the many challenges posed by the huge data volumes produced by the new generation of astronomical instruments there is also the search for rare and peculiar objects. Unsupervised outlier detection algorithms may provide a viable solution. In this work we compare the performances of six...
Available

Anomaly Detection in Astrophysics: A Comparison Between Unsupervised Deep and Machine Learning on KiDS Data

D’Addona, Maurizio; Riccio, Giuseppe; Cavuoti, Stefano; Tortora, Crescenzo; Brescia, Massimo

Pages: 225 –244

[Every field of Science is undergoing unprecedented changes in the discovery process, and Astronomy has been a main player in this transition since the beginning. The ongoing and future large and complex multi-messenger sky surveys impose a wide exploiting of robust and efficient automated...

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