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An $n$-th order Lagrangian Forward Model for Large-Scale Structure
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abstract
A forward model of matter and biased tracers at arbitrary order in Lagrangian perturbation theory (LPT) is presented. The forward model contains the complete LPT displacement field at any given order in perturbations, as well as all relevant bias operators at that order and leading order in derivatives. The construction is done for any expansion history and does not rely on the Einstein-de Sitter approximation. A large subset of higher-derivative bias operators is also included. As validation test, we compare the $n$LPT-predicted matter density field and that from N-body simulations using the same initial conditions. For simulations using a cutoff in the initial conditions, we find subpercent agreement up to scales of $k\sim 0.2 h\,{\rm Mpc}^{-1}$. We also find subpercent agreement with full simulations without cutoff, both for the power spectrum and nonlinear $\sigma_8$-inference, when allowing for the effective sound speed. The application to biased tracers (halos) has already been presented in a recent paper (arXiv:2009.14176).
Forward citations
Cited by 3 Pith papers
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CHEFT: A Hybrid Effective Field Theory halo model
CHEFT recovers matter power to percent level and weighted tracers to ~3–5% by expressing the halo-halo spectrum as a sum of collapsed HEFT operators with probabilistic mass-dependent biases.
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DISCO-DJ II: a differentiable particle-mesh code for cosmology
A GPU-accelerated, differentiable particle-mesh N-body code achieves per-cent-level power-spectrum accuracy with few time steps and recovers sigma_8 plus initial conditions from a noisy mock field.
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Equivalence of the field-level inference and conventional analyses on large scales
A joint power spectrum, bispectrum and trispectrum analysis achieves the same precision on the density amplitude as field-level inference for halos on large scales.
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