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Realistic and Informative Simulations with machine learnING

Project description

Improved simulations for stargazing

Our interest in astronomy dates back to ancient times. Boosted with developments and improvements as well as the use of more advanced equipment and in-depth knowledge of the sciences, astronomy remains popular to this day. Today, astronomical research greatly depends on simulations. Unfortunately, there is no way to practically measure the realism factor in simulation, and numerical simulations tend to be too slow and expensive for prototyping new techniques or improving statistical significance. The EU-funded RISING project will address these issues by developing a framework comprising machine learning tools for a number of uses, which will find instantaneous application on dynamic simulations of star clusters and hydrodynamical simulations of their parent clouds.

Coordinator

UNIVERSITA DEGLI STUDI DI PADOVA
Net EU contribution
€ 255 768,00
Address
Via 8 Febbraio 2
35122 Padova
Italy

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Region
Nord-Est Veneto Padova
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00

Partners (1)

Partner

Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.

UNIVERSITE DE MONTREAL
Canada
Net EU contribution
€ 0,00
Address
Cp 6128 Station Centre Ville
H3C3J7 Montreal

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Activity type
Higher or Secondary Education Establishments
Other funding
€ 164 031,36