Infrared Resummation for Biased Tracers in Redshift Space
Mikhail M. Ivanov, Sergey Sibiryakov
TL;DR
This work develops an IR-safe framework to model redshift-space distortions and bias within time-sliced perturbation theory (TSPT), enabling controlled resummation of non-linear BAO damping in biased tracers. By mapping real-space correlators to redshift space via a 1D fictitious flow, the authors derive leading and next-to-leading order IR resummation formulas for power spectra and bispectra, including deterministic bias through a velocity-derivative operator basis. The approach yields explicit expressions for the dressed linear spectrum and loop corrections, with a practical implementation strategy that leverages wiggly/smooth decompositions and operator exponentiation, and it shows improved agreement with N-body data over linear or LO-resummed predictions. The framework is generalizable to higher-point functions, supports real- and redshift-space analyses, and provides a robust theoretical baseline for BAO studies and full-shape analyses in redshift space.
Abstract
We incorporate the effects of redshift space distortions and non-linear bias in time-sliced perturbation theory (TSPT). This is done via a new method that allows to map cosmological correlation functions from real to redshift space. This mapping preserves a transparent infrared (IR) structure of the theory and provides us with an efficient tool to study non-linear infrared effects altering the pattern of baryon acoustic oscillations (BAO) in redshift space. We give an accurate description of the BAO by means of a systematic resummation of Feynman diagrams guided by well-defined power counting rules. This establishes IR resummation within TSPT as a robust and complete procedure and provides a consistent theoretical model for the BAO feature in the statistics of biased tracers in redshift space.
