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Tuesday, 17 January 2012, 14:00 in P8445B
Prof. Levon Pogosian (SFU)
Fables of reconstruction: controlling bias in the dark energy equation of state
We develop an efficient, non-parametric Bayesian method for reconstructing the time evolution of the dark energy equation of state w(z) from observational data. Of particular importance is the choice of prior, which must be chosen carefully to minimise variance and bias in the reconstruction. Using a principal component analysis, we show how a correlated prior can be used to create a smooth reconstruction and also avoid bias in the mean behaviour of w(z). We test our method using Wiener reconstructions based on Fisher matrix projections, and also against more realistic MCMC analyses of simulated data sets for Planck and a Euclid-like mission.
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Modified by Andrei Frolov <frolov@sfu.ca> on 2023-11-01