ExoMAC
Financiado
Exoplanets Molecular Atmospheric Composition
"The search for and characterization of exoplanets are among the most active and rapidly advancing fields in modern astrophysics. To date, more than 4000 exoplanets have been detected, spanning wide ranges in physical, orbital and...
"The search for and characterization of exoplanets are among the most active and rapidly advancing fields in modern astrophysics. To date, more than 4000 exoplanets have been detected, spanning wide ranges in physical, orbital and stellar parameters, and with a great variety of system architectures. Understanding the causes of exoplanet diversity and variety is a stated goal of the next-generation of ESA/NASA missions. In this context, I propose to develop the project ""Exoplanets Molecular Atmospheric Composition"" (ExoMAC), together with the Instituto de Astrofisica de Canarias (IAC) under the supervision of Dr. Enric Pallé. The project consists of the following Scientific Objectives: SO1: The complete and consistent (C&C) analyses of individual planets for measuring the absolute abundances of all the main carbon and oxygen-bearing molecules, metallicity down to less than 0.5 dex and precise C/O down to 0.1 dex in a handful of exoplanet atmospheres. The C&C analyses will provide the first empirical constraints on the possible formation and evolutionary paths of exoplanets; SO2: The development of a convolutional neural network (CNN) for the automated classification of newly-released TESS light-curves for the discovery and classification of new exoplanet populations. This CNN will lead to the discovery of more than 10000 transiting exoplanets, among which to select the prime targets for spectroscopic characterization with current and next-generation facilities. The C&C analyses propose a novel approach to leverage the information obtained with multiple instruments and observing techniques through a bayesian framework. We will adopt an updated version of the TauREx code to enable consistent retrievals, coupled with deep convolutional generative adversarial networks to speed up the likelihood sampling."
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Duración del proyecto: 31 meses
Fecha Inicio: 2020-03-20
Fecha Fin: 2022-11-08
Fecha Fin: 2022-11-08
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2022-11-08
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
MSCA-IF-2019:
Individual Fellowships
Cerrada
hace 5 años
Presupuesto
El presupuesto total del proyecto asciende a
161K€
Líder del proyecto
INSTITUTO DE ASTROFISICA DE CANARIAS
Investigación y desarrollo organismos publicos
Perfil tecnológico
TRL
3-4
650K
Perfil tecnológico
TRL
3-4
650K