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Turning noise into signal: learning from the scatter in the Hubble diagram

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The supernova Hubble diagram residual contains valuable information on both the present matter power spectrum and its growth history. In this paper we show that this information can be retrieved with precision by combining both peculiar velocity and weak-lensing analysis on the data. To wit, peculiar velocity induces correlations on the nearby supernovae while lensing induces a non-Gaussian dispersion in faraway objects. We show that both effects have almost orthogonal degeneracies and discuss how they can be extracted simultaneously from the data. We analyze the JLA supernova catalog in a 14-dimensional parameter space, assuming a flexible growth-rate index gamma. We arrive at the following marginalized constraints: sigma8 = $1.16^{+0.23}_{-0.47}$ and gamma = $0.80^{+0.29}_{-0.34}$. We note that these constraints complement well the ones obtained from other data sets. Assuming instead GR as the correct gravitation theory (and thus gamma = 0.55), the constraints in sigma8 tighten further: sigma8 = $0.89^{+0.18}_{-0.21}$.


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