From <i>Hubble</i> to snap parameters: a Gaussian process reconstruction
J. F. Jesus, D. Benndorf, A. A. Escobal, S. H. Pereira
Abstract
ABSTRACT By using recent H(z) and supernovae Type Ia (SNe Ia) data, we reconstruct the evolution of kinematic parameters H(z), q(z), jerk, and snap, using a model-independent, non-parametric method, namely, the Gaussian processes. Throughout the present analysis, we have allowed for a spatial curvature prior, based on Planck 18 constraints. In the case of SNe Ia, we modify a python package (gapp) in order to obtain the reconstruction of the fourth derivative of a function, thereby allowing us to obtain the snap from comoving distances. Furthermore, using a method of importance sampling, we combine H(z) and SNe Ia reconstructions in order to find joint constraints for the kinematic parameters. We find for the current values of the parameters: H0 = 67.2 ± 6.2 km s−1 Mpc−1, $q_0 = -0.54^{+0.06}_{-0.05}$, $j_0=0.94^{+0.20}_{-0.18}$, and $s_0=-0.62^{+0.26}_{-0.25}$ at 1σ c.l. We find that these reconstructions are compatible with the predictions from flat lambda-cold dark matter model, at least for 2σ confidence intervals.