Weak Lensing Shear Measurements Research Articles

Euclid preparation. LIII. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling

is a weak lensing shear measurement method developed for and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies, sampling the posterior distribution of galaxy parameters via Markov chain Monte Carlo, and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by We quantified the scientific performance through high-fidelity images based on the Flagship simulations and emulation of the VIS images, realistic clustering with a mean surface number density of $ arcmin^ for galaxies, and $ arcmin^ for stars, and a diffraction-limited chromatic PSF with a full width at half maximum of $ $ and spatial variation across the field of view. measured objects with a density of $ arcmin^ in $4500 deg^2 $. The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed in future work). We found measurement multiplicative and additive biases of $m_1=(-3.6 $, $m_2=(-4.3 $, $c_1=(-1.78 $, and $c_2=(0.09 $; a large detection bias with a multiplicative component of $1.2 $ and an additive component of $-3 $; and a measurement PSF leakage of $ $ and $ $. When model bias is suppressed, the obtained measurement biases are close to requirement and largely dominated by undetected faint galaxies ($-5 $). Although significant, model bias will be straightforward to calibrate given its weak sensitivity on galaxy morphology parameters. is publicly available at

FORKLENS: Accurate weak-lensing shear measurement with deep learning

Context. Weak gravitational lensing is one of the most important probes of the nature of dark matter and dark energy. In order to extract cosmological information from next-generation weak lensing surveys (e.g., Euclid, Roman, LSST, and CSST) as much as possible, accurate measurements of weak lensing shear are required. Aims. There are existing algorithms to measure the weak lensing shear on imaging data, which have been successfully applied in previous surveys. In the meantime, machine learning (ML) has been widely recognized in various astrophysics applications in modeling and observations. In this work, we present a fully deep-learning-based approach to measuring weak lensing shear accurately. Methods. Our approach comprises two modules. The first one contains a convolutional neural network (CNN) with two branches for taking galaxy images and point spread function (PSF) simultaneously, and the output of this module includes the galaxy’s magnitude, size, and shape. The second module includes a multiple-layer neural network (NN) to calibrate weak-lensing shear measurements. We name the program FORKLENS and make it publicly available online. Results. Applying FORKLENS to CSST-like mock images, we achieve consistent accuracy with traditional approaches (such as moment-based measurement and forward model fitting) on the sources with high signal-to-noise ratios (S/N > 20). For the sources with S/N < 10, FORKLENS exhibits an ~36% higher Pearson coefficient on galaxy ellipticity measurements. Conclusions. After adopting galaxy weighting, the shear measurements with FORKLENS deliver accuracy levels to 0.2%. The whole procedure of FORKLENS is automated and costs about 0.7 milliseconds per galaxy, which is appropriate for adequately taking advantage of the sky coverage and depth of the upcoming weak lensing surveys.

Weak gravitational lensing measurements of Abell 2744 using JWST and shear measurement algorithm pyRRG-JWST

ABSTRACT We update the publicly available weak lensing shear measurement algorithm pyRRG for the JWST, and apply it to UNCOVER DR1 imaging of galaxy cluster Abell 2744. At short wavelengths (${\lt}2.5\, \mu$m), shear measurements are consistent between independent observations through different JWST bandpasses, and calibrated within 1.5 per cent of those from the Hubble Space Telescope. At longer wavelengths, shear is underestimated by ∼5 per cent, probably due to coarser pixellization. We model the spatially varying point spread function using WebbPSF, whose moments are within 0.05 of real stars near the centre of the mosaic, where there are sufficient stars to also generate an empirical model. We measure shear from up to 162 galaxies arcmin−2 to derive a map of dark plus baryonic mass with 12 arcsec (55 kpc) spatial resolution. All code, catalogues, and maps are available from https://github.com/davidharvey1986/pyRRG.

The MillenniumTNG Project: the impact of baryons and massive neutrinos on high-resolution weak gravitational lensing convergence maps

ABSTRACT We study weak gravitational lensing convergence maps produced from the MillenniumTNG simulations by direct projection of the mass distribution on the past backwards lightcone of a fiducial observer. We explore the lensing maps over a large dynamic range in simulation mass and angular resolution, allowing us to establish a clear assessment of numerical convergence. By comparing full physics hydrodynamical simulations with corresponding dark-matter-only runs, we quantify the impact of baryonic physics on the most important weak lensing statistics. Likewise, we predict the impact of massive neutrinos reliably far into the non-linear regime. We also demonstrate that the ‘fixed & paired’ variance suppression technique increases the statistical robustness of the simulation predictions on large scales not only for time slices but also for continuously output lightcone data. We find that both baryonic and neutrino effects substantially impact weak lensing shear measurements, with the latter dominating over the former on large angular scales. Thus, both effects must explicitly be included to obtain sufficiently accurate predictions for stage IV lensing surveys. Reassuringly, our results agree accurately with other simulation results where available, supporting the promise of simulation modelling for precision cosmology far into the non-linear regime.

Deep-field Metacalibration

We introduce deep-field metacalibration, a new technique that reduces the pixel noise in metacalibration estimators of weak lensing shear signals by using a deeper imaging survey for calibration. In standard metacalibration, when estimating the object's shear response, extra noise is added to correct the effect of shearing the noise in the image, increasing the uncertainty on shear estimates by ~ 20%. Our new deep-field metacalibration technique leverages a separate, deeper imaging survey to calculate calibrations with less degradation in image noise. We demonstrate that weak lensing shear measurement with deep-field metacalibration is unbiased up to second-order shear effects. We provide algorithms to apply this technique to imaging surveys and describe how to generalize it to shear estimators that rely explicitly on object detection (e.g., metacalibration). For the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the improvement in weak lensing precision will depend on the somewhat unknown details of the LSST Deep Drilling Field (DDF) observations in terms of area and depth, the relative point-spread function properties of the DDF and main LSST surveys, and the relative contribution of pixel noise vs. intrinsic shape noise to the total shape noise in the survey. We conservatively estimate that the degradation in precision is reduced from 20% for metacalibration to ~ 5% or less for deep-field metacalibration, which we attribute primarily to the increased source density and reduced pixel noise contributions to the overall shape noise. Finally, we show that the technique is robust to sample variance in the LSST DDFs due to their large area, with the equivalent calibration error being ~ 0.1%. The deep-field metacalibration technique provides higher signal-to-noise weak lensing measurements while still meeting the stringent systematic error requirements of future surveys.

One spectrum to cure them all: signature from early Universe solves major anomalies and tensions in cosmology

Acoustic peaks in the Cosmic Microwave Background (CMB) temperature spectrum as observed by the Planck satellite appear to be smoother than our expectation from the standard model lensing effect. This anomalous effect can be also mimicked by a spatially closed Universe with a very low value of Hubble constant that consequently aggravates the already existing discordance between cosmological observations. We reconstruct a signature from the early Universe, a particular form of oscillation in the primordial spectrum of quantum fluctuations with a characteristic frequency, that solves all these anomalies. Interestingly, we find this form of the primordial spectrum resolves or substantially subsides, various tensions in the standard model of cosmology in fitting different observations, namely Planck CMB, clustering and weak lensing shear measurements from several large scale structure surveys, local measurements of Hubble constant, and recently estimated age of the Universe from globular clusters. We support our findings phenomenologically, by proposing an analytical form of the primordial spectrum with similar features and demonstrate that it agrees remarkably well with various combinations of cosmological observations. We support further our findings theoretically, by introducing a single scalar field potential for inflation that can generate such a form of the primordial spectrum.

Weak gravitational lensing shear measurement with FPFS: analytical mitigation of noise bias and selection bias

ABSTRACT Dedicated ‘Stage IV’ observatories will soon observe the entire extragalactic sky, to measure the ‘cosmic shear’ distortion of galaxy shapes by weak gravitational lensing. To measure the apparent shapes of those galaxies, we present an improved version of the Fourier Power Function Shapelets (FPFS) shear measurement method. This now includes analytic corrections for sources of bias that plague all shape measurement algorithms: Including noise bias (due to noise in non-linear combinations of observable quantities) and selection bias (due to sheared galaxies being more or less likely to be detected). Crucially, these analytic solutions do not rely on calibration from external image simulations. For isolated galaxies, the small residual ${\sim}10^{-3}$ multiplicative bias and ${\lesssim}10^{-4}$ additive bias now meet science requirements for Stage IV experiments. FPFS also works accurately for faint galaxies and robustly against stellar contamination. Future work will focus on deblending overlapping galaxies. The code used for this paper can process ${\gt}1000$ galaxy images per CPU second and is available from https://github.com/mr-superonion/FPFS.

The wide-field multiband imaging and slitless spectroscopy survey to be carried out by the Survey Space Telescope of China Manned Space Program

<p indent=0mm>The 2 m-aperture Survey Space Telescope (also known as the China Space Station Telescope, CSST) is a major science project of China Manned Space Program. It is expected to start science operations around 2024 and has a nominal mission lifetime of <sc>10 years.</sc> During observations, CSST will fly independently in the same orbit as the space station while maintaining a large distance apart. It can dock with the space station for refueling and servicing as scheduled or as needed. With a Cook-type three-mirror anastigmat design, CSST can achieve superior image quality within a large field of view (FoV), which gives it an advantage for survey observations. Being an off-axis telescope without any obstruction, its point spread function (PSF) is not affected by diffraction of mirror support structures and is thus helpful for weak-lensing shear measurements. The radius encircling 80% energy of the PSF within CSST’s central 1.1 square degrees of FoV is required to be no more than 0.15″, including all wavefront errors in the optics and instruments and dynamical effects such as the telescope’s attitude control and vibration. CSST will be launched with 5 first-generation instruments including a survey camera, a terahertz receiver, a multichannel imager, an integral field spectrograph, and a cool planet imaging coronagraph. The survey camera is equipped with 30 9k×9k detectors for science observations, each with a filter or grating mounted above, a defocused 9k×9k detector for flux calibration in r band, 8 640×512 near-infrared detectors, fine guide sensors, and wavefront sensors. The primary task of CSST is to carry out a high-resolution large-area multiband imaging and slitless spectroscopy survey covering the wavelength range of <sc>255–1000 nm.</sc> Precision cosmology is the main science driver of the survey, and, therefore, the main area of sky selected for observation is at median-to-high galactic latitude and median-to-high ecliptic latitude. It will take the survey camera roughly <sc>7 years</sc> of operation accumulated over <sc>10 years</sc> of orbital time to image roughly 17500 square degrees of the sky in NUV, u, g, r, i, z, and y bands and take slitless spectroscopy of the same sky in 3 bands. The point-source 5σ limiting magnitudes in g and r bands can reach 26 (AB mag) or higher. The spectral resolution (<italic>R</italic>=<italic>λ</italic>/Δ<italic>λ</italic>) of the slitless spectrograph is specified to be on average no less than 200, and the wide-band-equivalent limiting magnitudes in GV <sc>(400–620 nm)</sc> and GI <sc>(620–1000 nm)</sc> bands will reach 23 or higher. In addition, a number of deep fields will be selected for more observations to reach at least one magnitude deeper than the wide-area survey. The combined advantage of its angular resolution, depth, wavelength range, capability of both imaging and spectroscopy and large-area sky coverage makes the CSST survey highly competitive, and, at the same time, its observations are also highly complementary with other large projects of its time, such as Vera Rubin Observatory, Euclid, and Roman Space Telescope. These projects will provide extremely rich datasets for potential breakthroughs in studies from the solar system to cosmology and beyond.

The point spread function reconstruction – II. The smooth PCA

ABSTRACT Accurate shear measurement is a key topic in weak lensing community. Point spread function (PSF), which smears the observed galaxy image, plays one of the main roles in the systematic errors in shear measurement and must be treated carefully to avoid bias and errors in cosmological parameters. In this paper, we present new PSF measurement methods, Smooth-PCA (SPCA) and Improved-SPCA (iSPCA), which can reconstruct smooth PSFs with high efficiency. Our methods decompose the star images into smooth principal components by using the Expectation-Maximization-PCA (EMPCA) method, and the smooth principal components are composed by Moffatlets basis functions, which are derived from the Moffat function. We demonstrate our approaches based on simulated Moffat PSFs and phosim star images. The constructed smooth principal components show flexible and efficient as the same as EMPCA, and have more stable patterns than EMPCA under noises contamination. We then check the reconstruction accuracy on the shape of PSFs. We find that our methods are able to reconstruct the PSFs at the same precision as the EMPCA method that indicates and iSPCA are promising for weak lensing shear measurement.

Weak-lensing shear measurement with machine learning

Cosmic shear, that is weak gravitational lensing by the large-scale matter structure of the Universe, is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe requires an extremely accurate measurement of the shapes of millions of galaxies based on imaging data. Crucially, the shear measurement must address and compensate for a range of interwoven nuisance effects related to the instrument optics and detector, noise in the images, unknown galaxy morphologies, colors, blending of sources, and selection effects. This paper explores the use of supervised machine learning as a tool to solve this inverse problem. We present a simple architecture that learns to regress shear point estimates and weights via shallow artificial neural networks. The networks are trained on simulations of the forward observing process, and take combinations of moments of the galaxy images as inputs. A challenging peculiarity of the shear measurement task, in terms of machine learning applications, is the combination of the noisiness of the input features and the requirements on the statistical accuracy of the inverse regression. To address this issue, the proposed training algorithm minimizes bias over multiple realizations of individual source galaxies, reducing the sensitivity to properties of the overall sample of source galaxies. Importantly, an observational selection function of these source galaxies can be straightforwardly taken into account via the weights. We first introduce key aspects of our approach using toy-model simulations, and then demonstrate its potential on images mimicking Euclid data. Finally, we analyze images from the GREAT3 challenge, obtaining competitively low multiplicative and additive shear biases despite the use of a simple training set. We conclude that the further development of suited machine learning approaches is of high interest to meet the stringent requirements on the shear measurement in current and future surveys. We make a demonstration implementation of our technique publicly available.

Analytical noise bias correction for weak lensing shear analysis with ERA

Highly precise weak lensing shear measurement is required for statistical weak gravitational lensing analysis such as cosmic shear measurement to achieve severe constraint on the cosmological parameters. For this purpose, the accurate shape measurement of background galaxies is absolutely important in which any systematic error in the measurement should be carefully corrected. One of the main systematic error comes from photon noise which is Poisson noise of flux from the atmosphere(noise bias). We investigate how the photon noise makes a systematic error in shear measurement within the framework of ERA method we developed in earlier papers and gives a practical correction method. The method is tested by simulations with real galaxy images with various conditions and it is confirmed that it can correct $80 \sim 90\%$ of the noise bias except for galaxies with very low signal to noise ratio.

Weak Lensing Study in VOICE Survey II: Shear Bias Calibrations

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical $ugri$ imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg$^2$ down to $r_\mathrm{AB}$$\sim$26 mag. In the companion paper by Fu et al. (2018), we present the weak lensing shear measurements for $r$-band images with seeing $\le$ 0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function (PSF) and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of $\sim$3.0%. We study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of $\sim$0.3%. Further analysis shows that galaxies with lower signal-to-noise ratio (SNR) are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighboring galaxies, we find that although most have been rejected in the shape measurement procedure, about one third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to $\sim$0.2% of the multiplicative bias. Such a bias can be removed by further eliminating these neighboring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys.

Radio weak lensing shear measurement in the visibility domain – II. Source extraction

This paper extends the method introduced in Rivi et al. (2016b) to measure galaxy ellipticities in the visibility domain for radio weak lensing surveys. In that paper we focused on the development and testing of the method for the simple case of individual galaxies located at the phase centre, and proposed to extend it to the realistic case of many sources in the field of view by isolating visibilities of each source with a faceting technique. In this second paper we present a detailed algorithm for source extraction in the visibility domain and show its effectiveness as a function of the source number density by running simulations of SKA1-MID observations in the band 950-1150 MHz and comparing original and measured values of galaxies' ellipticities. Shear measurements from a realistic population of 10^4 galaxies randomly located in a field of view of 1 deg^2 (i.e. the source density expected for the current radio weak lensing survey proposal with SKA1) are also performed. At SNR >= 10, the multiplicative bias is only a factor 1.5 worse than what found when analysing individual sources, and is still comparable to the bias values reported for similar measurement methods at optical wavelengths. The additive bias is unchanged from the case of individual sources, but is significantly larger than typically found in optical surveys. This bias depends on the shape of the uv coverage and we suggest that a uv-plane weighting scheme to produce a more isotropic shape could reduce and control additive bias.

On Using a Space Telescope to Detect Weak-lensing Shear

Ignoring redshift dependence, the statistical performance of a weak-lensing survey is set by two numbers: the effective shape noise of the sources, which includes the intrinsic ellipticity dispersion and the measurement noise, and the density of sources that are useful for weak-lensing measurements. In this paper, we provide some general guidance for weak-lensing shear measurements from a “generic” space telescope by looking for the optimum wavelength bands to maximize the galaxy flux signal-to-noise ratio (S/N) and minimize ellipticity measurement error. We also calculate an effective galaxy number per square degree across different wavelength bands, taking into account the density of sources that are useful for weak-lensing measurements and the effective shape noise of sources. Galaxy data collected from the ultra-deep UltraVISTA Ks-selected and R-selected photometric catalogs (Muzzin et al. ) are fitted to radially symmetric Sérsic galaxy light profiles. The Sérsic galaxy profiles are then stretched to impose an artificial weak-lensing shear, and then convolved with a pure Airy Disk PSF to simulate imaging of weak gravitationally lensed galaxies from a hypothetical diffraction-limited space telescope. For our model calculations and sets of galaxies, our results show that the peak in the average galaxy flux S/N, the minimum average ellipticity measurement error, and the highest effective galaxy number counts all lie around the K-band near 2.2 μm.

The third data release of the Kilo-Degree Survey and associated data products

The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope. It aims to image 1500 square degrees in four filters (ugri). The core science driver is mapping the large-scale matter distribution in the Universe, using weak lensing shear and photometric redshift measurements. Further science cases include galaxy evolution, Milky Way structure, detection of high-redshift clusters, and finding rare sources such as strong lenses and quasars. Here we present the third public data release (DR3) and several associated data products, adding further area, homogenized photometric calibration, photometric redshifts and weak lensing shear measurements to the first two releases. A dedicated pipeline embedded in the Astro-WISE information system is used for the production of the main release. Modifications with respect to earlier releases are described in detail. Photometric redshifts have been derived using both Bayesian template fitting, and machine-learning techniques. For the weak lensing measurements, optimized procedures based on the THELI data reduction and lensfit shear measurement packages are used. In DR3 stacked ugri images, weight maps, masks, and source lists for 292 new survey tiles (~300 sq.deg) are made available. The multi-band catalogue, including homogenized photometry and photometric redshifts, covers the combined DR1, DR2 and DR3 footprint of 440 survey tiles (447 sq.deg). Limiting magnitudes are typically 24.3, 25.1, 24.9, 23.8 (5 sigma in a 2 arcsec aperture) in ugri, respectively, and the typical r-band PSF size is less than 0.7 arcsec. The photometric homogenization scheme ensures accurate colors and an absolute calibration stable to ~2% for gri and ~3% in u. Separately released are a weak lensing shear catalogue and photometric redshifts based on two different machine-learning techniques.

Practical Weak-lensing Shear Measurement with Metacalibration

Abstract Metacalibration is a recently introduced method to accurately measure weak gravitational lensing shear using only the available imaging data, without need for prior information about galaxy properties or calibration from simulations. The method involves distorting the image with a small known shear, and calculating the response of a shear estimator to that applied shear. The method was shown to be accurate in moderate-sized simulations with galaxy images that had relatively high signal-to-noise ratios, and without significant selection effects. In this work we introduce a formalism to correct for both shear response and selection biases. We also observe that for images with relatively low signal-to-noise ratios, the correlated noise that arises during the metacalibration process results in significant bias, for which we develop a simple empirical correction. To test this formalism, we created large image simulations based on both parametric models and real galaxy images, including tests with realistic point-spread functions. We varied the point-spread function ellipticity at the five-percent level. In each simulation we applied a small few-percent shear to the galaxy images. We introduced additional challenges that arise in real data, such as detection thresholds, stellar contamination, and missing data. We applied cuts on the measured galaxy properties to induce significant selection effects. Using our formalism, we recovered the input shear with an accuracy better than a part in a thousand in all cases.

Prediction of galaxy ellipticities and reduction of shape noise in cosmic shear measurements

The intrinsic scatter in the ellipticities of galaxies about the mean shape, known as noise, is the most important source of noise in weak lensing shear measurements. Several approaches to reducing shape noise have recently been put forward, using information beyond photometry, such as radio polarization and optical spectroscopy. Here we investigate how well the intrinsic ellipticities of galaxies can be predicted using other, exclusively photometric parameters. These parameters (such as galaxy colours) are already available in the data and do not necessitate additional, often expensive observations. We apply two regression techniques, generalized additive models (GAM) and projection pursuit regression (PPR) to the publicly released data catalog of galaxy properties from CFHTLenS. In our simple analysis we find that the individual galaxy ellipticities can indeed be predicted from other photometric parameters to better precision than the scatter about the mean ellipticity. This means that without additional observations beyond photometry the ellipticity contribution to the shear can be measured to higher precision, comparable to using a larger sample of galaxies. Our best-fit model, achieved using PPR, yields a gain equivalent to having 114.3% more galaxies. Using only parameters unaffected by lensing (e.g.~surface brightness, colour), the gain is only ~12%.

Weak-lensing mass calibration of redMaPPer galaxy clusters in Dark Energy Survey Science Verification data

We use weak-lensing shear measurements to determine the mean mass of optically selected galaxy clusters in Dark Energy Survey Science Verification data. In a blinded analysis, we split the sample of more than 8,000 redMaPPer clusters into 15 subsets, spanning ranges in the richness parameter $5 \leq \lambda \leq 180$ and redshift $0.2 \leq z \leq 0.8$, and fit the averaged mass density contrast profiles with a model that accounts for seven distinct sources of systematic uncertainty: shear measurement and photometric redshift errors; cluster-member contamination; miscentering; deviations from the NFW halo profile; halo triaxiality; and line-of-sight projections. We combine the inferred cluster masses to estimate the joint scaling relation between mass, richness and redshift, $\mathcal{M}(\lambda,z) \varpropto M_0 \lambda^{F} (1+z)^{G}$. We find $M_0 \equiv \langle M_{200\mathrm{m}}\,|\,\lambda=30,z=0.5\rangle=\left[ 2.35 \pm 0.22\ \rm{(stat)} \pm 0.12\ \rm{(sys)} \right] \cdot 10^{14}\ M_\odot$, with $F = 1.12\,\pm\,0.20\ \rm{(stat)}\, \pm\, 0.06\ \rm{(sys)}$ and $G = 0.18\,\pm\, 0.75\ \rm{(stat)}\, \pm\, 0.24\ \rm{(sys)}$. The amplitude of the mass-richness relation is in excellent agreement with the weak-lensing calibration of redMaPPer clusters in SDSS by Simet et al. (2016) and with the Saro et al. (2015) calibration based on abundance matching of SPT-detected clusters. Our results extend the redshift range over which the mass-richness relation of redMaPPer clusters has been calibrated with weak lensing from $z\leq 0.3$ to $z\leq0.8$. Calibration uncertainties of shear measurements and photometric redshift estimates dominate our systematic error budget and require substantial improvements for forthcoming studies.

Line-of-sight effects in strong lensing: putting theory into practice

We present a simple method to accurately infer line of sight (LOS) integrated lensing effects for galaxy scale strong lens systems through image reconstruction. Our approach enables us to separate weak lensing LOS effects from the main strong lens deflector. We test our method using mock data and show that strong lens systems can be accurate probes of cosmic shear with a precision on the shear terms of ± 0.003 (statistical error) for an HST-like dataset. We apply our formalism to reconstruct the lens COSMOS 0038+4133 and its LOS. In addition, we estimate the LOS properties with a halo-rendering estimate based on the COSMOS field galaxies and a galaxy-halo connection. The two approaches are independent and complementary in their information content. We find that when estimating the convergence at the strong lens system, performing a joint analysis improves the measure by a factor of two compared to a halo model only analysis. Furthermore the constraints of the strong lens reconstruction lead to tighter constraints on the halo masses of the LOS galaxies. Joint constraints of multiple strong lens systems may add valuable information to the galaxy-halo connection and may allow independent weak lensing shear measurement calibrations.

Shear nulling after PSF Gaussianisation: Moment-based weak lensing measurements with subpercent noise bias

Current optical imaging surveys for cosmology are covering large areas of sky. To exploit the statistical power of these surveys for weak lensing measurements requires shape measurement methods with subpercent systematic errors. We introduce a new weak lensing shear measurement algorithm, Shear Nulling after PSF Gaussianisation (SNAPG), designed to avoid the noise biases that affect most other methods. SNAPG operates on images that have been convolved with a kernel that renders the Point Spread Function (PSF) a circular Gaussian, and uses weighted second moments of the sources. The response of such second moments to a shear of the pre-seeing galaxy image can be predicted analytically, allowing us to construct a shear nulling scheme that finds the shear parameters for which the observed galaxies are consistent with an unsheared, isotropically oriented population of sources. The inverse of this nulling shear is then an estimate of the gravitational lensing shear. We identify the uncertainty of the estimated centre of each galaxy as the source of noise bias, and incorporate an approximate estimate of the centroid covariance into the scheme. We test the method on extensive suites of simulated galaxies of increasing complexity, and find that it is capable of shear measurements with multiplicative bias below 0.5 percent.