Genetic algorithm reconstructs single-field inflationary models with features in the scalar power spectrum that fit Planck 2018 CMB data better by Δχ² ≲ -10 and suggest alternative background parameters.
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Gaussian Process Regression on mock GW siren catalogues reconstructs comoving distance and derivatives, showing that derivative diagnostics at specific redshifts best separate cosmological models while background data alone does not.
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Reconstructing inflationary features on large scales using genetic algorithm
Genetic algorithm reconstructs single-field inflationary models with features in the scalar power spectrum that fit Planck 2018 CMB data better by Δχ² ≲ -10 and suggest alternative background parameters.
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Gaussian Process Reconstruction of Cosmological Parameters with Gravitational Wave Sirens using Machine Learning
Gaussian Process Regression on mock GW siren catalogues reconstructs comoving distance and derivatives, showing that derivative diagnostics at specific redshifts best separate cosmological models while background data alone does not.