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2016

The Gaussian streaming model and Lagrangian effective field theory

Vlah, Zvonimir, Castorina, Emanuele, White, Martin

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We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion.

After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order.
We discuss the connection to the Gaussian peaks formalism.
We compare the ingredients of the GSM to a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum.

The Gaussian streaming model and Lagrangian effective field theory · Around

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