Prospects for recovering galaxy intrinsic shapes from projected quantities

Abstract

The distribution of three dimensional intrinsic galaxy shapes has been a longstanding open question. The difficulty stems from projection effects meaning one must rely on statistical methods applied to galaxy samples to infer intrinsic shape distributions. Theoretical work using analytical galaxy potentials suggests a relationship between galaxy intrinsic shape (as defined by its "triaxiality", in practice a proxy for how prolate a galaxy is) and the intrinsic misalignment angle between kinematic and morphological axes (Ψ int ). This relationship reduces the number of unknowns, providing more reliable inferred intrinsic shape distributions than methods using photometry alone.Here we explore the connection between intrinsic shape and stellar kinematics using cosmological hydrodynamical simulations from the Illustris project. The strongest relationship we find is that galaxy intrinsic flattening is correlated with specific angular momentum ( j) with high j galaxies being flatter than galaxies with low specific angular momentum. Our analysis shows that, although the majority of kinematically misaligned galaxies exhibit prolate shapes, examples of kinematically aligned prolate galaxies are also present. Clearly a direct correspondence between prolate shape and minor-axis rotation (often referred to as "prolate rotation") is not present in Illustris. Thus, we demonstrate that the assumption of a simple relationship between Ψ int and intrinsic shape commonly employed in shape recovery studies is not valid for Illustris galaxies. We suggest improvements on the method as well as some alternative methods for future work in this area.

The stellar halos of ETGs in the IllustrisTNG simulations: The photometric and kinematic diversity of galaxies at large radii

“…with p < 0.9). This result agrees with the analysis of Bassett & Foster (2019) of Illustris galaxies, among which they found many triaxial and prolate objects with small Ψ. Although we can not draw conclusions on the shape distribution of the real galaxies, Fig.…”

“…We do this by performing a selection in intrinsic shape, and reject all galaxies with intermediate to major axis ratio p < 0.6 at r ∼ 1 R e . This choice is motivated by the fact that the intrinsic shape distribution of real galaxies is known (Weijmans et al 2014;Foster et al 2017;Li et al 2018;Ene et al 2018) although with large uncertainties (Bassett & Foster 2019), and galaxies with p < 0.6 are rare, even among the slow rotators. By applying this selection criterion we obtain our final sample of simulated ETG galaxies, 1114 objects in TNG100 and 80 in TNG50.…”

The intricate link between galaxy dynamics and intrinsic shape (or why so-called prolate rotation is a misnomer)

“…The results presented herein were originally published in Bassett & Foster (2019). This research was supported by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013.…”

“…Such a relationship reduces the number of unknowns, possibly providing more reliable inferred intrinsic shape distributions than methods using imaging alone. In Bassett & Foster (2019), we explored the connection between galaxy intrinsic shape and stellar kinematics using cosmological hydrodynamical simulations from the Illustris project. This contribution summarizes one key result on the complex relationship between galaxy intrinsic shape and the intrinsic kinematic misalignment in Illustris.…”

SimSpin—Constructing mock IFS kinematic data cubes

“…The mock images produced can be passed through the same software tools that observers use to give consistent comparisons and also allows for the incorporation of observational limitations, such as the effects of the atmosphere that can artificially distort the observed line-of-sight (LOS) velocities. This approach is already being pursued by the SAMI (the Sydney-AAO Multi-object Integral field spectrograph survey; Croom et al 2012;Bryant et al 2015) and MaNGA (Mapping Nearby Galaxies at Apache Point; Bundy et al 2015;Blanton et al 2017) teams (see, e.g., Lagos et al 2018b;Bassett & Foster 2019;Duckworth et al 2020). This alone suggests that a tool for creating such data products in a publicly accessible and repeatable way is advantageous for the community.…”