Reconstructing the interaction between dark energy and dark matter using Gaussian Processes

摘要

We present a nonparametric approach to reconstruct the interaction betweendark energy and dark matter directly from SNIa Union 2.1 data using Gaussianprocesses, which is a fully Bayesian approach for smoothing data. In thismethod, once the equation of state ($w$) of dark energy is specified, theinteraction can be reconstructed as a function of redshift. For the decayingvacuum energy case with $w=-1$, the reconstructed interaction is consistentwith the standard $\Lambda$CDM model, namely, there is no evidence for theinteraction. This also holds for the constant $w$ cases from $-0.9$ to $-1.1$and for the Chevallier-Polarski-Linder (CPL) parametrization case. If theequation of state deviates obviously from $-1$, the reconstructed interactionexists at $95\%$ confidence level. This shows the degeneracy between theinteraction and the equation of state of dark energy when they get constraintsfrom the observational data.