Speaker
Description
Type Ia supernovae are among the brightest objects in the sky, and the estimation of their distances to Earth have been used as proof that the universe is expanding at an accelerated rate. They are the result of the explosion of a carbon-oxygen white dwarf, in a binary system with another star, whose nature is still unknown.
In this project, Machine Learning tools such as Gaussian Processes and clustering are going to be used in an attempt to divide a sample of nearby type Ia supernovae in different subgroups, based on the evolution of their B – V color with time. If they exist, these subgroups could hint at their progenitor systems and improve the estimations of the dust extinction surrounding them and with it obtain more accurate distances for better cosmological constraints.
