The Predictive Power of Computational Astrophysics As a Discovery Tool: Proceedings of the 362nd Symposium of the International Astronomical Union Virtual Meeting, Originally Planned for Chamonix, France 8-12 November, 202

Bisikalo, Dmitry (Editor)/ Wiebe, Dimitri (Editor)/ Boily, Christian (Editor)

ISBN 10: 1108490662 / ISBN 13: 9781108490665

Edité par Cambridge Univ Pr, 2023

A propos de cet article

400 pages. 9.53x6.54x0.39 inches. In Stock.

N° de réf. du vendeur x-1108490662

Détails bibliographiques

• Titre: The Predictive Power of Computational Astrophysics As a Discovery Tool: Proceedings of the 362nd Symposium of the International Astronomical Union Virtual Meeting, Originally Planned for Chamonix, France 8-12 November, 202
• Éditeur: Cambridge Univ Pr
• Date de parution: 2023
• Langue: anglais
• ISBN à 10 chiffres: 1108490662
• ISBN à 13 chiffres: 9781108490665
• Reliure: Hardcover
• État de l'article: Brand New

A propos de ce titre

Synopsis

A new paradigm for scientific discovery through computational tools now permeates every aspect of astronomical research. Computational astrophysics combines modern computational methods, novel hardware designs, advanced algorithms, original software implementations, and associated technologies to discover new phenomena and to make predictions in astronomy. The proceedings of IAU Symposium 362 summarizes ongoing developments in computational astrophysics through astronomers in diverse fields sharing their knowledge and approaches. It focuses on computational methods applied to speed up and broaden the scope of scientific studies, such as finding trends in observational data, high performance computing, automated search algorithms, and model predictability. Experts discuss a palette of challenging informational and technical developments, with the goal of coordinating their efforts and the improvement of techniques in pursuit of a wide range of astronomical studies, including fluid dynamics in star and galaxy evolution, exoplanets, gravitational waves, numerical relativity, data mining, and much more.