IATE 20350
INSTITUTO DE ASTRONOMIA TEORICA Y EXPERIMENTAL
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
CosmoML: A Machine Learning method to measure the cosmological parameters
Autor/es:
ROMERO, M. DOMÍNGUEZ; MARTIN DE LOS RIOS
Lugar:
Carguese
Reunión:
Workshop; XIIIth School of Cosmology, Cargese (IESC); 2017
Institución organizadora:
IESC
Resumen:
In this work we present the first measurement of the spatial distribution of the cosmological parameters performed with a joined analysis of the latest Cosmic Microwave Background (CMB) data from Planck and the supernova data of JLA. In order to treat all the data in an homogeneous way and to reduce the cpu-time involved in the parameters estimation, we developed a machine learning algorithm that was trained with simulated data and tested comparing with the results of the standard montecarlo estimation.
