The technique uses principal component analysis and a combination of information criteria to identify real features in the data, and tailors the fitting functions to pick up trends and smooth over noise. It is simple, quick and relatively accurate, and involves no expensive explorations of parameter space. We present a new nonparametric method which can accurately reconstruct a wide variety of dark energy behavior with no prior assumptions about it. ![]() ![]() With so few physically motivated models, future dark energy studies cannot only be based on constraining a dark energy parameter space. ![]() ![]() An important issue in cosmology is reconstructing the effective dark energy equation of state directly from observations.
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