Implementing wavelet technique for reconstructing the equation of state of Dark Energy
ORAL
Abstract
Acceleration of the universe can be caused by a dark energy component with a negative equation of state, w, which can be redshift dependent. In this work, we investigate the efficiency of using wavelets for reconstructing the dark energy equation of state from supernovae data. We consider several theoretically motivated redshift dependencies of w and study how well these dependencies can be recovered from simulated data.
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