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Register a new userExtended lens reconstructions with Grale: exploiting time domain, substructural and weak-lensing information
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The information about the mass density of galaxy clusters provided by the gravitational lens effect has inspired many inversion techniques. In this article, updates to the previously introduced method in Grale are described, and explored in a number of examples. The first looks into a different way of incorporating time delay information, not requiring the unknown source position. It is found that this avoids a possible bias that leads to over-focusing the images, i.e. providing source position estimates that lie in a considerably smaller region than the true positions. The second is inspired by previous reconstructions of the cluster of galaxies MACS J1149.6+2223, where a multiply-imaged background galaxy contained a supernova, SN Refsdal, of which four additional images were produced by the presence of a smaller cluster galaxy. The inversion for the cluster as a whole, was not able to recover sufficient detail interior to this quad. We show how constraints on such different scales, from the entire cluster to a single member galaxy, can now be used, allowing such small scale substructures to be resolved. Finally, the addition of weak lensing information to this method is investigated. While this clearly helps recover the environment around the strong lensing region, the mass sheet degeneracy may make a full strong and weak inversion difficult, depending on the quality of the ellipticity information at hand. We encounter ring-like structure at the boundary of the two regimes, argued to be the result of combining strong and weak lensing constraints, possibly affected by degeneracies.
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Recent studies have shown that the number counts of convergence peaks N(kappa) in weak lensing (WL) maps, expected from large forthcoming surveys, can be a useful probe of cosmology. We follow up on this finding, and use a suite of WL convergence maps, obtained from ray-tracing N-body simulations, to study (i) the physical origin of WL peaks with different heights, and (ii) whether the peaks contain information beyond the convergence power spectrum P_ell. In agreement with earlier work, we find that high peaks (with amplitudes >~ 3.5 sigma, where sigma is the r.m.s. of the convergence kappa) are typically dominated by a single massive halo. In contrast, medium-height peaks (~0.5-1.5 sigma) cannot be attributed to a single collapsed dark matter halo, and are instead created by the projection of multiple (typically, 4-8) halos along the line of sight, and by random galaxy shape noise. Nevertheless, these peaks dominate the sensitivity to the cosmological parameters w, sigma_8, and Omega_m. We find that the peak height distribution and its dependence on cosmology differ significantly from predictions in a Gaussian random field. We directly compute the marginalized errors on w, sigma_8, and Omega_m from the N(kappa) + P_ell combination, including redshift tomography with source galaxies at z_s=1 and z_s=2. We find that the N(kappa) + P_ell combination has approximately twice the cosmological sensitivity compared to P_ell alone. These results demonstrate that N(kappa) contains non-Gaussian information complementary to the power spectrum.
We show that the so-called post-Born effects of weak lensing at 4th order are equivalent to lens-lens couplings in the Born Approximation. We demonstrate this by explicitly showing the equivalence of the canonical weak lensing approach at 4th order using the anisotropy remapping method, to that of the 4th order calculation of the lens-lens coupling effects using the Boltzmann equation approach that was first developed in [Phys. Rev. D89, 123006]. Furthermore, we argue that to incorporate true post-Born effects, i.e. taking into account non-straight photon paths, require the addition of a photon deflection term which has not been taken into account in the canonical formalism nor the Boltzmann method.
Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three methods: Kaiser-Squires (KS), Wiener filter, and GLIMPSE. KS is a direct inversion, not accounting for survey masks or noise. The Wiener filter is well-motivated for Gaussian density fields in a Bayesian framework. GLIMPSE uses sparsity, aiming to reconstruct non-linearities in the density field. We compare these methods with several tests using public Dark Energy Survey (DES) Science Verification (SV) data and realistic DES simulations. The Wiener filter and GLIMPSE offer substantial improvements over smoothed KS with a range of metrics. Both the Wiener filter and GLIMPSE convergence reconstructions show a 12 per cent improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods abilities to find mass peaks, we measure the difference between peak counts from simulated {Lambda}CDM shear catalogues and catalogues with no mass fluctuations (a standard data vector when inferring cosmology from peak statistics); the maximum signal-to-noise of these peak statistics is increased by a factor of 3.5 for the Wiener filter and 9 for GLIMPSE. With simulations we measure the reconstruction of the harmonic phases; the phase residuals concentration is improved 17 per cent by GLIMPSE and 18 per cent by the Wiener filter. The correlation between reconstructions from data and foreground redMaPPer clusters is increased 18 per cent by the Wiener filter and 32 per cent by GLIMPSE.
Using the first three years of data from the Dark Energy Survey, we use ratios of small-scale galaxy-galaxy lensing measurements around the same lens sample to constrain source redshift uncertainties, intrinsic alignments and other nuisance parameters of our model. Instead of using a simple geometric approach for the ratios, we use the full modeling of the galaxy-galaxy lensing measurements, including the corresponding integration over the power spectrum and the contributions from intrinsic alignments and lens magnification. We perform extensive testing of the small-scale shear ratio (SR) modeling by studying the impact of different effects such as the inclusion of baryonic physics, non-linear biasing, halo occupation distribution descriptions and lens magnification, among others, and using realistic $N$-body simulations. We validate the robustness of our constraints in the data by using two independent lens samples, and by deriving constraints using the corresponding large-scale ratios for which the modeling is simpler. The DES Y3 results demonstrate how the ratios provide significant improvements in constraining power for several nuisance parameters in our model, especially on source redshift calibration and intrinsic alignments (IA). For source redshifts, SR improves the constraints from the prior by up to 38% in some redshift bins. Such improvements, and especially the constraints it provides on IA, translate to tighter cosmological constraints when SR is combined with cosmic shear and other 2pt functions. In particular, for the DES Y3 data, SR improves $S_8$ constraints from cosmic shear by up to 31%, and for the full combination of probes (3$times$2pt) by up to 10%. The shear ratios presented in this work are used as an additional likelihood for cosmic shear, 2$times$2pt and the full 3$times$2pt in the fiducial DES Y3 cosmological analysis.
In the near future, ultra deep observations of galaxy clusters with HST or JWST will uncover $300-1000$ lensed multiple images, increasing the current count per cluster by up to an order of magnitude. This will further refine our view of clusters, leading to a more accurate and precise mapping of the total and dark matter distribution in clusters, and enabling a better understanding of background galaxy population and their luminosity functions. However, to effectively use that many images as input to lens inversion will require a re-evaluation of, and possibly upgrades to the existing methods. In this paper we scrutinize the performance of the free-form lens inversion method Grale in the regime of $150-1000$ input images, using synthetic massive galaxy clusters. Our results show that with an increasing number of input images, Grale produces improved reconstructed mass distributions, with the fraction of the lens plane recovered at better than $10%$ accuracy increasing from $40-50%$ for $sim!!150$ images to $65%$ for $sim!1000$ images. The reconstructed time delays imply a more precise measurement of $H_0$, with $lesssim 1%$ bias. While the fidelity of the reconstruction improves with the increasing number of multiple images used as model constraints, $sim 150$ to $sim 1000$, the lens plane rms deteriorates from $sim 0.11$ to $sim 0.28$. Since lens plane rms is not necessarily the best indicator of the quality of the mass reconstructions, looking for an alternative indicator is warranted.
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