Abstract
An accurate theoretical template for the galaxy power spectrum is key for the success of ongoing and future spectroscopic surveys. We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters. To that end, we initiate a blinded challenge to infer cosmological parameters from the redshift-space power spectrum of high-resolution mock catalogs mimicking the BOSS galaxy sample but covering a 100 times larger cumulative volume. This gigantic simulation volume allows us to separate systematic bias due to theoretical modeling from the statistical error due to sample variance. The challenge is to measure three unknown input parameters used in the simulation: the Hubble constant, the matter density fraction, and the clustering amplitude. We present analyses done by two independent teams, who have fitted the mock simulation data generated by yet another independent group. This allows us to avoid any confirmation bias by analyzers and to pin down possible tuning of the specific EFT implementations. Both independent teams have recovered the true values of the input parameters within subpercent statistical errors corresponding to the total simulation volume.
Highlights
Modern cosmology is becoming more mature as accumulating observational data become available
We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters
The input values of the cosmological parameters were unblinded after each team submitted its results for consensus data cuts. We present these results in the original form prepared by either team independently. Both teams have chosen to analyze the mean power spectrum over ten realizations, with the covariance estimated from the inverse sum of covariances for ten single boxes, C
Summary
Modern cosmology is becoming more mature as accumulating observational data become available. To form rich structures in the late Universe (dark matter), as well as the accelerating cosmic expansion (dark energy), together filling the majority of the cosmological energy budget. Of crucial importance from a theoretical point of view is our ability to prepare an accurate model template with which one can confront such observational data for interpretation. Since a larger survey means a smaller statistical error, the relative contribution from the systematic error arising from the inaccuracy of the template is more important. Given the gigantic area coverage and depth of ambitious future programs, we need to find an accurate theoretical framework to predict the observed large-scale structure to attain their full potential to infer the underlying theory governing the Universe
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