Cosmology Inference from Biased Tracers using the EFT-based Likelihood. (arXiv:1906.07143v2 [astro-ph.CO] UPDATED)
<a href="http://arxiv.org/find/astro-ph/1/au:+Elsner_F/0/1/0/all/0/1">Franz Elsner</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Schmidt_F/0/1/0/all/0/1">Fabian Schmidt</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Jasche_J/0/1/0/all/0/1">Jens Jasche</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Lavaux_G/0/1/0/all/0/1">Guilhem Lavaux</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Nguyen_N/0/1/0/all/0/1">Nhat-Minh Nguyen</a>
The effective-field-theory (EFT) approach to the clustering of galaxies and
other biased tracers allows for an isolation of the cosmological information
that is protected by symmetries, in particular the equivalence principle, and
thus is robust to the complicated dynamics of dark matter, gas, and stars on
small scales. All existing implementations proceed by making predictions for
the lowest-order $n$-point functions of biased tracers, as well as their
covariance, and comparing with measurements. Recently, we presented an
EFT-based expression for the conditional probability of the density field of a
biased tracer given the matter density field, which in principle combines
information from arbitrarily high order $n$-point functions. Here, we report
results based on this likelihood by applying it to halo catalogs in real space,
specifically on the inference of the power spectrum normalization $sigma_8$.
We include bias terms up to second order as well as the leading
higher-derivative term. For a cutoff value of $Lambda = 0.1 h,{rm
Mpc}^{-1}$, we recover the ground-truth value of $sigma_8$ to within 95% CL
for different halo samples and redshifts. We discuss possible sources for the
remaining systematic bias in $sigma_8$ as well as future developments.
The effective-field-theory (EFT) approach to the clustering of galaxies and
other biased tracers allows for an isolation of the cosmological information
that is protected by symmetries, in particular the equivalence principle, and
thus is robust to the complicated dynamics of dark matter, gas, and stars on
small scales. All existing implementations proceed by making predictions for
the lowest-order $n$-point functions of biased tracers, as well as their
covariance, and comparing with measurements. Recently, we presented an
EFT-based expression for the conditional probability of the density field of a
biased tracer given the matter density field, which in principle combines
information from arbitrarily high order $n$-point functions. Here, we report
results based on this likelihood by applying it to halo catalogs in real space,
specifically on the inference of the power spectrum normalization $sigma_8$.
We include bias terms up to second order as well as the leading
higher-derivative term. For a cutoff value of $Lambda = 0.1 h,{rm
Mpc}^{-1}$, we recover the ground-truth value of $sigma_8$ to within 95% CL
for different halo samples and redshifts. We discuss possible sources for the
remaining systematic bias in $sigma_8$ as well as future developments.
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