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Apr 4, 2024
Abstract
Supernovas (SNs) have been one of the most studied events in astronomy. However, there are still no models capable of describing this phenomenon in a general and accurate way. These models generally seek to describe a single type of supernova, requires multiple parameter’s values and often do not distinguish between the different light bands of the same curve. Structured grammatical evolution allows
the generation of a model with data and a given basal structure, which can be designed considering the nature of the problem for which we are looking for a model. In this case, with some mathematical assumptions we can generate a symbolic regression to obtain a model for different types of SNs and for each light band. We can also use this algorithm to fit the parametric model of the supernova and obtain the value of the variables needed to model it.
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