Nonlinear Reconstruction of the Velocity Field

TL;DR

This paper introduces a novel velocity reconstruction method that improves accuracy over standard techniques by leveraging displacement estimation and transfer functions, with promising applications in cosmology.

Contribution

The paper presents a new velocity reconstruction approach based on displacement estimation and transfer functions, outperforming standard methods in simulations.

Findings

Better cross-correlation coefficient

Reduced velocity misalignment

Smaller amplitude difference

Abstract

We propose a new velocity reconstruction method based on the displacement estimation by recently developed methods. The velocity is first reconstructed by transfer functions in Lagrangian space and then mapped into Eulerian space. High resolution simulations are used to test the performance. We find that the new reconstruction method outperforms the standard velocity reconstruction in the sense of better cross-correlation coefficient, less velocity misalignment and smaller amplitude difference. We conclude that this new method has the potential to improve the large-scale structure sciences involving a velocity reconstruction, such as kinetic Sunyaev-Zel'dovich measurement and supernova cosmology.