Direct reconstruction of dark energy

An important issue in cosmology is reconstructing the effective dark energyequation of state directly from observations. With so few physically motivated models, future dark energystudies cannot only be based on constraining a dark energy parameter space. We present a new nonparametric method which can accurately reconstruct a wide variety of dark energybehavior with no prior assumptions about it. It is simple, quick and relatively accurate, and involves no expensive explorations of parameter space. The technique uses principal component analysis and a combination of information criteriato identify real features in the data, and tailors the fitting functionsto pick up trends and smooth over noise. We find that we can constrain a large variety of w(z) models to within 10%-20% at redshifts z ≲ 1 using just SNAP-quality data.