Project description
On an astrophysics mission to explore star formation
Big Data and hybrid machine learning methods will be used to explore the largest, panchromatic data collection of young stellar objects. Paving the path towards data-intensive science applications in modern astrophysics, the EU-funded NEMESIS project will improve our understanding of star formation. Recent evidence suggests that planets form synchronously rather than sequentially to their host stars, indicating a rapid early evolution of star–planet systems. NEMESIS will determine the characteristic transitions that describe each phase of star formation. Specifically, it will review the current classification scheme and its characteristic timescales so that it is concurrent with the most recent observational and theoretical constraints.
Fields of science
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesphysical sciencesastronomyastrophysics
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesphysical sciencesastronomystellar astronomy
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programme(s)
Funding Scheme
RIA - Research and Innovation action
Coordinator
1010 Wien
Austria
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Participants (2)
1211 Geneve
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1121 Budapest
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