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EFCLASS

The effective fluid approach for f(R) and Horndeski models.

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We present the effective fluid approach for f(R) and Horndeski models based on the papers 1811.02469 and 1904.06294, by Rubén Arjona, Savvas Nesseris and Wilmar Cardona. Here we provide the numerical codes used in the papers to implement the effective fluid approach in the popular Boltzmann CLASS code (https://github.com/lesgourg/class_public). Our modifications to the CLASS code, called EFCALSS, can also be found at this website (https://members.ift.uam-csic.es/savvas.nesseris/efclass.html) and at this GitHub page (https://github.com/wilmarcardonac/EFCLASS).

Genetic Algorithms

Code that implements a Genetic Algorithm regression approach in Mathematica.

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Comments:

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  1. Run the Genetic Algorithm (GA) code with different grammars, adjust the crossover and mutation rates.

  2. Can run with both uncorrelated and correlated data by changing the likelihood.

  3. Error estimates using the path-integral approach.

  4. Operative in one dimension but can be easily extended in more dimensions.

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