Large data set of lensed quasars: higher accuracy on H0? The angular structures viewpoint

peer reviewedThanks to forthcoming large-scale surveys, a tremendous number of strong lenses will be discovered in the coming years. The gain in accuracy on H0 from such a large population of lensed quasars is a key question for the future of time-delay cosmography. In such context, lensed systems will have to be modeled in an automated way, with models that are sufficiently generic to apply to every lens. I explore the biases that may arise from unaccounted-for azimuthal structures in mass models. The non-modeled twists in lensing galaxies are expected to bias the shear inference but not H0. Disregarded ellipticity gradients, boxyness and discyness may impact the cosmological inference on a lens-by-lens basis. Nevertheless, the diversity of azimuthal mass profile in lenses balances the bias at a population level and the H0 inference can thus benefits from such large surveys

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

The impact of mass map truncation on strong lensing simulations

Strong gravitational lensing is a powerful tool to measure cosmological parameters and to study galaxy evolution mechanisms. However, quantitative strong lensing studies often require mock observations. To capture the full complexity of galaxies, the lensing galaxy is often drawn from high resolution, dark matter only or hydro-dynamical simulations. These have their own limitations, but the way we use them to emulate mock lensed systems may also introduce significant artefacts. In this work we identify and explore the specific impact of mass truncation on simulations of strong lenses by applying different truncation schemes to a fiducial density profile with conformal isodensity contours. Our main finding is that improper mass truncation can introduce undesired artificial shear. The amplitude of the spurious shear depends on the shape and size of the truncation area as well as on the slope and ellipticity of the lens density profile. Due to this effect, the value of H0 or the shear amplitude inferred by modelling those systems may be biased by several percents. However, we show that the effect becomes negligible provided that the lens projected map extends over at least 50 times the Einstein radius

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

peer reviewedMassive 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° with respect to the reference orientation at the Einstein radius, and of the shear by up to 20° 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 H0, up to 10 km s−1 Mpc−1. 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

TDCOSMO VIII: A key test of systematics in the hierarchical method of time-delay cosmography

peer reviewedThe largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of $H_0$. A Bayesian hierarchical framework has been proposed which combines lens systems with kinematic data, constraining the mass profile shape at a population level. The framework has been previously validated on a small sample of lensing galaxies drawn from hydro-simulations. The goal of this work is to expand the validation to a more general set of lenses consistent with observed systems, as well as confirm the capacity of the method to combine two lens populations: one which has time delay information and one which lacks time delays and has systematically different image radii. For this purpose, we generate samples of analytic lens mass distributions made of baryons+dark matter and fit the subsequent mock images with standard power-law models. Corresponding kinematics data are also emulated. The hierarchical framework applied to an ensemble of time-delay lenses allows us to correct the $H_0$ bias associated with model choice, finding $H_0$ within $1.5\sigma$ of the fiducial value. We then combine this set with a sample of corresponding lens systems which have no time delays and have a source at lower $z$, resulting in a systematically smaller image radius relative to their effective radius. The hierarchical framework successfully accounts for this effect, recovering a value of $H_0$ which is both more precise ($\sigma\sim2\%$) and more accurate ($0.7\%$ median offset) than the time-delay set alone. This result confirms that non-time-delay lenses can nonetheless contribute valuable constraining power to the determination of $H_0$ via their kinematic constraints, assuming they come from the same global population as the time-delay set

The ellipticity parameterization for an NFW profile: An overlooked angular structure in strong lens modeling

peer reviewedGalaxy-scale gravitational lenses are often modeled with two-component mass profiles where one component represents the stellar mass and the second is an NFW profile representing the dark matter. Outside of the spherical case, the NFW profile is costly to implement, and so it is approximated via two different methods; ellipticity can be introduced via the lensing potential (NFWp) or via the mass by approximating the NFW profile as a sum of analytical profiles (NFWm). While the NFWp method has been the default for lensing applications, it gives a different prescription of the azimuthal structure, which we show introduces ubiquitous gradients in ellipticity and boxiness in the mass distribution rather than having a constant elliptical shape. Because unmodeled azimuthal structure has been shown to be able to bias lens model results, we explore the degree to which this introduced azimuthal structure can affect the model accuracy. We construct input profiles using composite models using both the NFWp and NFWm methods and fit these mocks with a power-law elliptical mass distribution (PEMD) model with external shear. As a measure of the accuracy of the recovered lensing potential, we calculate the value of the Hubble parameter $H_0$ one would determine from the lensing fit. We find that the fits to the NFWp input return $H_0$ values which are systematically biased by about $3\%$ lower than the NFWm counterparts. We explore whether such an effect is attributable to the mass sheet transformation (MST) by using an MST-independent quantity, $\xi_2$. We show that, as expected, the NFWm mocks are degenerate with PEMD through an MST. For the NFWp, an additional bias is found beyond the MST due to azimuthal structures {\it exterior to the Einstein radius}. We recommend modelers use an NFWm prescription in the future, such that azimuthal structure can be introduced explicitly rather than implicitly

Exploiting the diversity of modeling methods to probe systematic biases in strong lensing analyses

peer reviewedChallenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly increased, from purely analytical methods, to pixelated and non-parametric ones, or ones based on deep learning. We embraced this diversity by selecting different software packages and use them to blindly model independently simulated Hubble Space Telescope (HST) imaging data. To overcome the difficulties arising from using different codes and conventions, we used the COde-independent Organized LEns STandard (COOLEST) to store, compare, and release all models in a self-consistent and human-readable manner. From an ensemble of six modeling methods, we studied the recovery of the lens potential parameters and properties of the reconstructed source. In particular, we simulated and inferred parameters of an elliptical power-law mass distribution embedded in a shear field for the lens, while each modeling method reconstructs the source differently. We find that, overall, both lens and source properties are recovered reasonably well, but systematic biases arise in all methods. Interestingly, we do not observe that a single method is significantly more accurate than others, and the amount of bias largely depends on the specific lens or source property of interest. By combining posterior distributions from individual methods using equal weights, the maximal systematic biases on lens model parameters inferred from individual models are reduced by a factor of 5.4 on average. We investigated a selection of modeling effects that partly explain the observed biases, such as the cuspy nature of the background source and the accuracy of the point spread function. This work introduces, for the first time, a generic framework to compare and ease the combination of models obtained from different codes and methods, which will be key to retain accuracy in future strong lensing analyses

TDCOSMO. VII. Boxyness/discyness in lensing galaxies : Detectability and impact on H0H_0

In the context of gravitational lensing, the density profile of lensing galaxies is often considered to be perfectly elliptical. Potential angular structures are generally ignored, except to explain flux ratios anomalies. Surprisingly, the impact of azimuthal structures on extended images of the source has not been characterized, nor its impact on the H0 inference. We address this task by creating mock images of a point source embedded in an extended source, lensed by an elliptical galaxy on which multipolar components are added to emulate boxy/discy isodensity contours. Modeling such images with a density profile free of angular structure allow us to explore the detectability of image deformation induced by the multipoles in the residual frame. Multipole deformations are almost always detectable for our highest signal-to-noise mock data. However the detectability depends on the lens ellipticity and Einstein radius, on the S/N of the data, and on the specific lens modeling strategy. Multipoles also introduce small changes to the time delays. We therefore quantify how undetected multipoles would impact H0 inference. When no multipoles are detected in the residuals, the impact on H0 for a given lens is in general less than a few km/s/Mpc, but in the worst case scenario, combining low S/N in the ring and large intrinsic boxyness/discyness, the bias on H0 can reach 10-12 km/s/Mpc. If we now look at the inference on H0 from a population of lensing galaxies, having a distribution of multipoles representative of what is found in the light-profile of elliptical galaxies, we then find a systematic bias on H0 < 1%. The comparison of our mock systems to the state-of-the-art time delay lens sample studied by the H0LiCOW and TDCOSMO collaborations, indicates that multipoles are currently unlikely to be a source of substantial systematic bias on the inferred value of H0 from time-delay lenses

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