Galaxy Intrinsic Alignments for LSST with the Multi-Estimator Method

Determining the properties of dark energy with weak gravitational lensing measurements is a primary science goal of Rubin Observatory's Legacy Survey of Space and Time (LSST), the global flagship ground-based astronomical imaging survey of the coming decade. Crucial to achieving this goal is to limit the modelling noise on LSST weak lensing arising from gaps in our understanding of the intrinsic alignment of galaxies. Intrinsic alignments (IA) are correlations in galaxy shapes which are believed to be caused by a combination of tidal effects, galaxy evolution, and environment. Weak gravitational lensing, on the other hand, occurs when mass along the line-of-sight distorts the trajectory of light from background galaxies and induces correlations in their observed shapes - much like those correlations due to IA. Reliably separating IA from lensing is thus challenging, but absolutely essential to extract cosmological information from weak lensing measurements. We will use the novel but proven Multi-Estimator Method (MEM) to measure the IA signal of galaxies from early LSST data. This method, created by the Project Lead, takes advantage of the fact that different estimators for extracting the ellipticity (or 'shape') of galaxies from image data are more or less sensitive to different radial regions (i.e. inner vs outer parts) of the galaxy light profile. IA impacts the observed galaxy ellipticity in a manner that varies across the galaxy light profile, whereas the weak lensing effect on galaxy ellipticity is uniform. MEM takes advantage of this difference to extract the IA signal. Having previously made a proof-of-concept application of this method using Dark Energy Survey galaxy shape measurements from standard estimators, we will develop bespoke shape estimators which are optimised to best measure IA using MEM. We will then apply these shape estimators to early data from LSST and thus measure the IA signal. Finally, we will use our measurement to minimise the IA noise in LSST weak lensing analysis, both by precisely determining the maximum residual level of IA in the weak lensing signal and by uniquely producing measurements of the parameters of state-of-the-art IA models for LSST weak lensing galaxies. Our work will enable early LSST weak lensing to probe signatures of dark energy, and will also pin down the parameters which describe the physical details of IA itself, offering unique insight into this astrophysical process.