Symmetries, Invariants and Generating Functions: Higher-order Statistics of Biased Tracers
Dipak Munshi

TL;DR
This paper uses symmetry principles and generating functions in perturbation theory to analyze higher-order statistics of biased tracers in cosmology, simplifying complex terms and extending previous bias models.
Contribution
It introduces a formalism that simplifies higher-order biasing terms and computes cumulant correlators for biased tracers using symmetry and perturbation theory.
Findings
Many extended symmetry terms do not contribute to higher-order statistics.
Vertices of biased tracers can be expressed in terms of underlying density and velocity vertices.
Perturbative results are valid at arbitrary order for tree-level contributions.
Abstract
Gravitationally collapsed objects are known to be biased tracers of an underlying density contrast. Using symmetry arguments, generalised biasing schemes have recently been developed to relate the halo density contrast with the underlying density contrast , divergence of velocity and their higher-order derivatives. This is done by constructing invariants such as . We show how the generating function formalism in Eulerian standard perturbation theory (SPT) can be used to show that many of the additional terms based on extended Galilean and Lifshitz symmetry actually do not make any contribution to the higher-order statistics of biased tracers. Other terms can also be drastically simplified allowing us to write the vertices associated with in terms of the vertices of and , the higher-order derivatives and the bias…
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