During the talk, I will give a brief review about my past and current projects
related with the possibility to observe the first stars by looking their final fate
as gamma-ray bursts or supernova. In special, I will discuss a current and
still on going project explained bellow.
With the next generation of optical and near-infrared (NIR) surveys, the
possibility to observe primordial stars becomes real. A fraction of these first
stars, with masses between ~ 140 and 260 solar mass, are expected to die
as pair-instability supernovae (PISN). We use the state of art of cosmological
simulations, to infer the predicted rate of PISN, and radiation hydrodynamical
simulations, to model the spectral energy distribution of PISN in realistic
circumstellar environments with Lyman absorption by the neutral intergalactic
medium. We then constructed a synthetic survey of supernovae light curves
as they should be observed by James Webb Space Telescope (JWST),
including all important characteristic of the experiment. We are capable to
provide a sample of FITS file that can be treated as the same way as a real
data. Future supernova surveys are expected to observe much more
supernovae than can be confirmed spectroscopically. Given the rare nature
of these events, it’s imperative to rely in some good photometric predictor,
in order to find suitable candidates for posterior spectroscopically
confirmation. Thus, using our synthetic sample, we perform a comprehensive
study of the best strategy capable to find these objects, estimate the redshift
and identify them photometrically. To do so, we are using a combination of
the best learning methods available, in special kernel principal components
analysis (kpca), fuzzy logic and genetic algorithms. Our methodology based
in KPCA already proved to have a higher accuracy only relying in
photometric information in the problem of Type Ia identification (Ishida, E.
and de Souza, R, MNRAS 2013,), with no need of redshift information.
We are developing the most realistic and complex framework, from far,
to study the best way to find the first supernovae. Being one of the most
promising approaches to drive the future searches of these objects.