The impact of Λ\LambdaCDM substructure and baryon-dark matter transition on the image positions of quad galaxy lenses

The positions of multiple images in galaxy lenses are related to the galaxy mass distribution. Smooth elliptical mass profiles were previously shown to be inadequate in reproducing the quad population. In this paper, we explore the deviations from such smooth elliptical mass distributions. Unlike most other work, we use a model-free approach based on the relative polar image angles of quads, and their position in 3D space with respect to the Fundamental Surface of Quads. The FSQ is defined by quads produced by elliptical lenses. We have generated thousands of quads from synthetic populations of lenses with substructure consistent with $\Lambda$CDM simulations, and found that such perturbations are not sufficient to match the observed distribution of quads relative to the FSQ. The result is unchanged even when subhalo masses are increased by a factor of ten, and the most optimistic lensing selection bias is applied. We then produce quads from galaxies created using two components, representing baryons and dark matter. The transition from the mass being dominated by baryons in inner radii to being dominated by dark matter in outer radii can carry with it asymmetries, which would affect relative image angles. We run preliminary experiments using lenses with two elliptical mass components with nonidentical axis ratios and position angles, perturbations from ellipticity in the form of nonzero Fourier coefficients $a_4$ and $a_6$, and artificially offset ellipse centers as a proxy for asymmetry at image radii. We show that combination of these effects is a promising way of accounting for quad population properties. We conclude that the quad population provides a unique and sensitive tool for constraining detailed mass distribution in the centers of galaxies.Comment: 18 pages, 15 figures, 2 table

Galaxy-lens determination of H0H_0: the effect of the ellipse+shear modeling assumption

Galaxy lenses are frequently modeled as an elliptical mass distribution with external shear and isothermal spheres to account for secondary and line-of-sight galaxies. There is statistical evidence that some fraction of observed quads are inconsistent with these assumptions, and require a dipole-like contribution to the mass with respect to the light. Simplifying assumptions about the shape of mass distributions can lead to the incorrect recovery of parameters such as $H_0$. We create several tests of synthetic quad populations with different deviations from an elliptical shape, then fit them with an ellipse+shear model, and measure the recovered values of $H_0$. Kinematic constraints are not included. We perform two types of fittings -- one with a single point source and one with an array of sources emulating an extended source. We carry out two model-free comparisons between our mock quads and the observed population. One result of these comparisons is a statistical inconsistency not yet mentioned in the literature: the image distance ratios with respect to the lens center of observed quads appear to span a much wider range than those of synthetic or simulated quads. Bearing this discrepancy in mind, our mock populations can result in biases on $H_0$ $\sim10\%$.Comment: 15 pages, 5 figures; to be published in MNRA

Consequences of the lack of azimuthal freedom in the modeling of lensing galaxies

Massive elliptical galaxies can display structures that deviate from a pure elliptical shape, such as a twist of the principal axis or variations in the axis ratio with galactocentric distance. Although satisfactory lens modeling is generally achieved without accounting for these azimuthal structures, the question about their impact on inferred lens parameters remains, in particular, on time delays as they are used in time-delay cosmography. This paper aims at characterizing these effects and quantifying their impact considering realistic amplitudes of the variations. We achieved this goal by creating mock lensing galaxies with morphologies based on two data sets: observational data of local elliptical galaxies, and hydrodynamical simulations of elliptical galaxies at a typical lens redshift. We then simulated images of the lensing systems with space-based data quality and modeled them in a standard way to assess the impact of a lack of azimuthal freedom in the lens model. We find that twists in lensing galaxies are easily absorbed in homoeidal lens models by a change in orientation of the lens up to 10{\deg} with respect to the reference orientation at the Einstein radius, and of the shear by up to 20{\deg} with respect to the input shear orientation. The ellipticity gradients, on the other hand, can introduce a substantial amount of shear that may impact the radial mass model and consequently bias $H_0$, up to 10 km/s/Mpc. However, we find that light is a good tracer of azimuthal structures, meaning that direct imaging should be capable of diagnosing their presence. This in turn implies that such a large bias is unlikely to be unaccounted for in standard modeling practices. Furthermore, the overall impact of twists and ellipticity gradients averages out at a population level. For the galaxy populations we considered, the cosmological inference remains unbiased.Comment: Accepted for publication in A&A, 19 page

Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematics analyses

Strong gravitational lensing is a powerful tool to provide constraints on galaxy mass distributions and cosmological parameters, such as the Hubble constant, $H_0$. Nevertheless, inference of such parameters from images of lensing systems is not trivial as parameter degeneracies can limit the precision in the measured lens mass and cosmological results. External information on the mass of the lens, in the form of kinematic measurements, is needed to ensure a precise and unbiased inference. Traditionally, such kinematic information has been included in the inference after the image modeling, using spherical Jeans approximations to match the measured velocity dispersion integrated within an aperture. However, as spatially resolved kinematic measurements become available via IFU data, more sophisticated dynamical modeling is necessary. Such kinematic modeling is expensive, and constitutes a computational bottleneck which we aim to overcome with our Stellar Kinematics Neural Network (SKiNN). SKiNN emulates axisymmetric modeling using a neural network, quickly synthesizing from a given mass model a kinematic map which can be compared to the observations to evaluate a likelihood. With a joint lensing plus kinematic framework, this likelihood constrains the mass model at the same time as the imaging data. We show that SKiNN's emulation of a kinematic map is accurate to considerably better precision than can be measured (better than $1\%$ in almost all cases). Using SKiNN speeds up the likelihood evaluation by a factor of $\sim 200$. This speedup makes dynamical modeling economical, and enables lens modelers to make effective use of modern data quality in the JWST era.Comment: (13 pages, 9 figures, submitted to Astronomy & Astrophysics

Galaxy-lens determination of <i>H</i>0: the effect of the ellipse + shear modelling assumption

ABSTRACT Galaxy lenses are frequently modelled as an elliptical mass distribution with external shear and isothermal spheres to account for secondary and line-of-sight galaxies. There is statistical evidence that some fraction of observed quads are inconsistent with these assumptions, and require a dipole-like contribution to the mass with respect to the light. Simplifying assumptions about the shape of mass distributions can lead to the incorrect recovery of parameters such as H0. We create several tests of synthetic quad populations with different deviations from an elliptical shape, then fit them with an ellipse + shear model, and measure the recovered values of H0. Kinematic constraints are not included. We perform two types of fittings – one with a single point source and one with an array of sources emulating an extended source. We carry out two model-free comparisons between our mock quads and the observed population. One result of these comparisons is a statistical inconsistency not yet mentioned in the literature: the image distance ratios with respect to the lens centre of observed quads appear to span a much wider range than those of synthetic or simulated quads. Bearing this discrepancy in mind, our mock populations can result in biases on H0$\sim 10{{\ \rm per\ cent}}$.</jats:p