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