GREAT3 results I: systematic errors in shear estimation and the impact of real galaxy morphology

We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically-varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially-varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by $\sim 1$ per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the S\'{e}rsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods' results support the simple model in which additive shear biases depend linearly on PSF ellipticity.Comment: 32 pages + 15 pages of technical appendices; 28 figures; submitted to MNRAS; latest version has minor updates in presentation of 4 figures, no changes in content or conclusion

GREAT3 results – I. Systematic errors in shear estimation and the impact of real galaxy morphology

We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by ∼1 per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the Sérsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods’ results support the simple model in which additive shear biases depend linearly on PSF ellipticity

GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology

We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by ∼1percent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the Sérsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods' results support the simple model in which additive shear biases depend linearly on PSF ellipticit

Consistent lensing and clustering in a low-S8 Universe with BOSS, DES Year 3, HSC Year 1, and KiDS-1000

We evaluate the consistency between lensing and clustering based on measurements from BOSS combined with galaxy-galaxy lensing from DES-Y3, HSC-Y1, KiDS-1000. We find good agreement between these lensing datasets. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck (S 8 = 0.83), and a Lensing cosmology (S 8 = 0.76). For a joint analysis limited to large scales, we find that both cosmologies provide an acceptable fit to the data. Full utilisation of the higher signal-to-noise small-scale measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic inconsistency parameter for each redshift bin, A, that decouples the lensing and clustering. With a wide range of scales, we find different results for the consistency between the two cosmologies. Limiting the analysis to the bins for which the impact of the lens sample selection is expected to be minimal, for the Lensing cosmology, the measurements are consistent with A=1; A = 0.91 ± 0.04 (A = 0.97 ± 0.06) using DES+KiDS (HSC). For the Planck case, we find a discrepancy: A = 0.79 ± 0.03 (A = 0.84 ± 0.05) using DES+KiDS (HSC). We demonstrate that a kSZ-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of small-scale measurements, but caution is still warranted given modelling uncertainties and foreground sample selection effects

Consistent lensing and clustering in a low-S8 Universe with BOSS, DES Year 3, HSC Year 1, and KiDS-1000

We evaluate the consistency between lensing and clustering based on measurements from Baryon Oscillation Spectroscopic Survey combined with galaxy-galaxy lensing from Dark Energy Survey (DES) Year 3, Hyper Suprime-Cam Subaru Strategic Program (HSC) Year 1, and Kilo-Degree Survey (KiDS)-1000. We find good agreement between these lensing data sets. We model the observations using the DARK EMULATOR and fit the data at two fixed cosmologies: Planck (S8 = 0.83), and a Lensing cosmology (S8 = 0.76). For a joint analysis limited to large scales, we find that both cosmologies provide an acceptable fit to the data. Full utilization of the higher signal-to-noise small-scale measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic inconsistency parameter for each redshift bin, A, that decouples the lensing and clustering. With a wide range of scales, we find different results for the consistency between the two cosmologies. Limiting the analysis to the bins for which the impact of the lens sample selection is expected to be minimal, for the Lensing cosmology, the measurements are consistent with A = 1; A = 0.91 ± 0.04 (A = 0.97 ± 0.06) using DES+KiDS (HSC). For the Planck case, we find a discrepancy: A = 0.79 ± 0.03 (A = 0.84 ± 0.05) using DES+KiDS (HSC). We demonstrate that a kinematic Sunyaev-Zeldovich-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of small-scale measurements; however, caution is still warranted given modelling uncertainties and foreground sample selection effects

Intrinsic alignments of group and cluster galaxies in photometric surveys

Intrinsic alignments of galaxies have been shown to contaminate weak gravitational lensing observables on linear scales, $r>$ 10 $h^{-1}$Mpc, but studies of alignments in the non-linear regime have thus far been inconclusive. We present an estimator for extracting the intrinsic alignment signal of galaxies around stacked clusters of galaxies from multiband imaging data. Our estimator removes the contamination caused by galaxies that are gravitationally lensed by the clusters and scattered in redshift space due to photometric redshift uncertainties. It uses posterior probability distributions for the redshifts of the galaxies in the sample and it is easily extended to obtain the weak gravitational lensing signal while removing the intrinsic alignment contamination. We apply this algorithm to groups and clusters of galaxies identified in the Sloan Digital Sky Survey `Stripe 82' coadded imaging data over $\sim 150$ deg$^2$. We find that the intrinsic alignment signal around stacked clusters in the redshift range $0.1<z<0.4$ is consistent with zero. In terms of the tidal alignment model of Catelan et al. (2001), we set joint constraints on the strength of the alignment and the bias of the lensing groups and clusters on scales between 0.1 and $10\,h^{-1}$ Mpc, $b_LC_1\rho_{\rm crit} = -2_{-14}^{+14} \times 10^{-4}$. This constrains the contamination fraction of alignment to lensing signal to the range between $[-18,23]$ per cent below scales of 1 $h^{-1}$ Mpc at 95 per cent confidence level, and this result depends on our photometric redshift quality and selection criteria used to identify background galaxies. Our results are robust to the choice of photometric band in which the shapes are measured ($i$ and $r$) and to centring on the Brightest Cluster Galaxy or on the geometrical centre of the clusters.Comment: 30 pages, 16 figures, published in MNRA

Bayesian earthquake dating and seismic hazard assessment using chlorine-36 measurements (BED v1)

Over the past twenty years, analyzing the abundance of the isotope chlorine-36 (36Cl) has emerged as a popular tool for geologic dating. In particular, it has been observed that 36Cl measurements along a fault plane can be used to study the timings of past ground displacements during earthquakes, which in turn can be used to improve existing seismic hazard assessment. This approach requires accurate simulations of 36Cl accumulation for a set of fault-scarp rock samples, which are 5 progressively exhumed during earthquakes, in order to infer displacement histories from 36Cl measurements. While the physical models underlying such simulations have continuously been improved, the inverse problem of recovering displacement histories from 36Cl measurements is still mostly solved on an ad-hoc basis. The current work resolves this situation by providing a MATLAB implementation of a fast, automatic, and flexible Bayesian Markov-chain Monte Carlo algorithm for the inverse problem, and provides a validation of the 36Cl approach to inference of earthquakes from the demise of the Last Glacial 10 Maximum until present. To demonstrate its performance, we apply our algorithm to a synthetic case to verify identifiability, and to the Fiamignano and Frattura faults in the Italian Apennines in order to infer their earthquake displacement histories and to provide seismic hazard assessments. The results suggest high variability in slip rates for both faults, and large displacements on the Fiamignano fault at times when the Colosseum and other ancient buildings in Rome were damaged

CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey

We present the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) that accurately determines a weak gravitational lensing signal from the full 154 deg^2 of deep multicolour data obtained by the CFHT Legacy Survey. Weak gravitational lensing by large-scale structure is widely recognized as one of the most powerful but technically challenging probes of cosmology. We outline the CFHTLenS analysis pipeline, describing how and why every step of the chain from the raw pixel data to the lensing shear and photometric redshift measurement has been revised and improved compared to previous analyses of a subset of the same data. We present a novel method to identify data which contributes a non-negligible contamination to our sample and quantify the required level of calibration for the survey. Through a series of cosmology-insensitive tests we demonstrate the robustness of the resulting cosmic shear signal, presenting a science-ready shear and photometric redshift catalogue for future exploitation