Thawing k-essence dark energy in the PAge space

A broad class of dark energy models can be written in the form of k-essence, whose Lagrangian density is a two-variable function of a scalar field phi and its kinetic energy X = 1/2 partial derivative(mu)phi partial derivative(mu)phi. In the thawing scenario, the scalar field becomes dynamic only when the Hubble friction drops below its mass scale in the late Universe. Thawing k-essence dark energy models can be randomly sampled by generating the Taylor expansion coefficients of its Lagrangian density from random matrices [Huang Z 2021 Phys. Rev. D 104 103533]. Reference [Huang Z 2021 Phys. Rev. D 104 103533] points out that the non-uniform distribution of the effective equation of state parameters (w(0), w(a)) of the thawing k-essence model can be used to improve the statistics of model selection. The present work studies the statistics of thawing k-essence in a more general framework that is Parameterized by the Age of the Universe (PAge) [Huang Z 2020 Astrophys. J. Lett. 892 L28]. For fixed matter fraction Omega(m), the random thawing k-essence models cluster in a narrow band in the PAge parameter space, providing a strong theoretical prior. We simulate cosmic shear power spectrum data for the Chinese Space Station Telescope optical survey, and compare the fisher forecast with and without the theoretical prior of thawing k-essence. For an optimal tomography binning scheme, the theoretical prior improves the figure of merit in PAge space by a factor of 3.3.

Automated summary

This study improves the statistical performance of model selection for thawing k-essence dark energy models by using the theoretical prior of these models. The thawing k-essence models cluster in a narrow band in the parameter space, providing a strong theoretical prior.