Gaussian processes reconstruction of dark energy from observational data
  In the present paper, we investigate the dark energy equation of state using
the Gaussian processes analysis method, without confining a particular
parametrization. The reconstruction is carried out by adopting the background
data including supernova and Hubble parameter, and perturbation data from the
growth rate. It suggests that the background and perturbation data both present
a hint of dynamical dark energy. However, the perturbation data have a more
promising potential to distinguish non-evolution dark energy including the
cosmological constant model. We also test the influence of some parameters on
the reconstruction. We find that the matter density parameter $\Omega_{m0}$ has
a slight effect on the background data reconstruction, but has a notable
influence on the perturbation data reconstruction. While the Hubble constant
presents a significant influence on the reconstruction from background data.
