Probabilistic Estimators of Lagrangian Shape Biases: Universal Relations and Physical Insights

TL;DR

This paper introduces new estimators for Lagrangian shape-biases, measures their relation to peak significance, and provides insights into galaxy shape formation and intrinsic alignments relevant for cosmology.

Contribution

The paper develops independent, object-specific estimators for Lagrangian shape-biases and applies them to dark-matter halos to understand shape formation processes.

Findings

Bias parameters are independent and measurable per object.

Universal linear relation between shape-bias and peak significance at high $ u$.

Evidence against galaxy shapes arising from post-formation tidal interactions.

Abstract

The intrinsic alignment of galaxies is a key factor in modeling weak-lensing observations and can serve as a valuable signal for both cosmological and astrophysical studies. Modelling this signal requires understanding how galaxy shapes form, and their relations to the large-scale gravitational field -- typically encoded in the value of large-scale shape-bias parameters. In this article we contribute to this topic in three ways: (i) developing new estimators of Lagrangian shape-biases (ii) applying them to measure the shape-biases of dark-matter halos (iii) interpreting these measurements to gain insight on the process of halo-shape formation. We show that our estimators produce results consistent with previous literature, and that they possess advantages with respect to previous methods, namely that the measurement of each bias parameter is completely independent from the others, and that bias parameters can be defined for each individual object. We measure universal relations between shape-bias parameters and peak-significance, $\nu$. This relation for the first-order shape-bias parameter is linear at high $\nu$, and converges to zero at low $\nu$, which we interpret as strong evidence against the proposed scenario according to which galaxy shapes arise due to post-formation interaction with the large-scale tidal-field. We anticipate our estimators to be very useful in analyzing hydrodynamical simulations to extract physical understandings of galaxy shape formation, as well as establishing priors on the values of intrinsic-alignment biases.