MG12 - Talk detail
 

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Abstract

Genetic algorithms and non-parametric Dark Energy reconstructions.

Genetic algorithms are being used in applied sciences as a stochastic method of problem-solving. Borrowing ideas from evolution of biological systems, they can act as efficient search algorithms in large problem spaces for which there is poor theoretical knowledge. We discuss how this scheme can be used in a cosmological context as an alternative non-parametric reconstruction approach, to determine Dark Energy parameters . The method is used to analyse supernova Ia data and provide fits for the temporal evolution of the equation of state.

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