Weak Lensing Publications

UNIONS: The impact of systematic errors on weak-lensing peak counts

Posted on July 7, 2022 by Samuel Farrens

Abstract

Context. The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is an ongoing deep photometric multi-band survey of the Northern sky. As part of UNIONS, the Canada-France Imaging Survey (CFIS) provides r-band data which we use to study weak-lensing peak counts for cosmological inference.
Aims. We assess systematic effects for weak-lensing peak counts and their impact on cosmological parameters for the UNIONS survey. In particular, we present results on local calibration, metacalibration shear bias, baryonic feedback, the source galaxy redshift estimate, intrinsic alignment, and the cluster member dilution.

Methods. For each uncertainty and systematic effect, we describe our mitigation scheme and the impact on cosmological parameter constraints. We obtain constraints on cosmological parameters from MCMC using CFIS data and MassiveNuS N-body simulations as a model for peak counts statistics.
Results. Depending on the calibration (local versus global, and the inclusion of the residual multiplicative shear bias), the mean matter density parameter Ωm can shift up to −0.024 (−0.5σ). We also see that including baryonic corrections can shift Ωm by +0.027 (+0.5σ) with respect to the DM-only simulations. Reducing the impact of the intrinsic alignment and cluster member dilution through signal-to-noise cuts can lead to a shift in Ωm of +0.027 (+0.5σ). Finally, with a mean redshift uncertainty of ∆z ̄ = 0.03, we see that the shift of Ωm (+0.001 which corresponds to +0.02σ) is not significant.

Conclusions. This paper investigates for the first time with UNIONS weak-lensing data and peak counts the impact of systematic effects. The value of Ωm is the most impacted and can shift up to ∼ 0.03 which corresponds to 0.5σ depending on the choices for each systematics. We expect constraints to become more reliable with future (larger) data catalogues, for which the current pipeline will provide a starting point. The code used to obtain the results is available in the following Github repository.

ShapePipe: a new shape measurement pipeline and weak-lensing application to UNIONS/CFIS data

Posted on July 7, 2022 by Samuel Farrens

Abstract

UNIONS is an ongoing collaboration that will provide the largest deep photometric survey of the Northern sky in four optical bands to date. As part of this collaboration, CFIS is taking r-band data with an average seeing of 0.65 arcsec, which is complete to magnitude 24.5 and thus ideal for weak-lensing studies. We perform the first weak-lensing analysis of CFIS r-band data over an area spanning 1700 deg2 of the sky. We create a catalogue with measured shapes for 40 million galaxies, corresponding to an effective density of 6.8 galaxies per square arcminute, and demonstrate a low level of systematic biases. This work serves as the basis for further cosmological studies using the full UNIONS survey of 4800 deg2 when completed. Here we present ShapePipe, a newly developed weak-lensing pipeline. This pipeline makes use of state-of-the-art methods such as Ngmix for accurate galaxy shape measurement. Shear calibration is performed with metacalibration. We carry out extensive validation tests on the Point Spread Function (PSF), and on the galaxy shapes. In addition, we create realistic image simulations to validate the estimated shear. We quantify the PSF model accuracy and show that the level of systematics is low as measured by the PSF residuals. Their effect on the shear two-point correlation function is sub-dominant compared to the cosmological contribution on angular scales <100 arcmin. The additive shear bias is below 5x10−4, and the residual multiplicative shear bias is at most 10−3 as measured on image simulations. Using COSEBIs we show that there are no significant B-modes present in second-order shear statistics. We present convergence maps and see clear correlations of the E-mode with known cluster positions. We measure the stacked tangential shear profile around Planck clusters at a significance higher than 4σ.

ShapePipe: A modular weak-lensing processing and analysis pipeline

Posted on July 6, 2022July 6, 2022 by Samuel Farrens

Abstract

We present the first public release of ShapePipe, an open-source and modular weak-lensing measurement, analysis, and validation pipeline written in Python. We describe the design of the software and justify the choices made. We provide a brief description of all the modules currently available and summarise how the pipeline has been applied to real Ultraviolet Near-Infrared Optical Northern Survey data. Finally, we mention plans for future applications and development. The code and accompanying documentation are publicly available on GitHub.

Early dark energy in the pre- and post-recombination epochs

Posted on January 11, 2022 by Valeria Pettorino

Abstract

Dark energy could play a role at redshifts $z ≫ O (1)$ . Many quintessence models possess scaling or attractor solutions where the fraction of dark energy follows the dominant component in previous epochs of the Universe’s expansion, or phase transitions may happen close to the time of matter-radiation equality. A non-negligible early dark energy (EDE) fraction around matter-radiation equality could contribute to alleviate the well-known $H_{0}$ tension. In this work, we constrain the fraction of EDE using two approaches: first, we use a fluid parameterization that mimics the plateaux of the dominant components in the past. An alternative tomographic approach constrains the EDE density in binned redshift intervals. The latter allows us to reconstruct the evolution of $Ω_{de} (z)$ before and after the decoupling of the cosmic microwave background (CMB) photons. We have employed Planck data 2018, the Pantheon compilation of supernovae of Type Ia (SNIa), data on galaxy clustering, the prior on the absolute magnitude of SNIa by SH0ES, and weak lensing data from $KiDS + VIKING - 450$ and DES-Y1. When we use a minimal parameterization mimicking the background plateaux, EDE has only a small impact on current cosmological tensions. We show how the constraints on the EDE fraction weaken considerably when its sound speed is allowed to vary. By means of our binned analysis we put very tight constraints on the EDE fraction around the CMB decoupling time, $≲ 0.4 %$ at $2 σ$ c.l. We confirm previous results that a significant EDE fraction in the radiation-dominated epoch loosens the $H_{0}$ tension, but tends to worsen the tension for $σ_{8}$ . A subsequent presence of EDE in the matter-dominated era helps to alleviate this issue. When both the SH0ES prior and weak lensing data are considered in the fitting analysis in combination with data from CMB, SNIa and baryon acoustic oscillations, the EDE fractions are constrained to be $≲ 2.6 %$ in the radiation-dominated epoch and $≲ 1.5 %$ in the redshift range $z \in (100, 1000)$ at $2 σ$ c.l. The two tensions remain with a statistical significance of $\sim 2 - 3 σ$ c.l.

Press release (in Italian) by MEDIA INAF is available here.

Starlet l1-norm for weak lensing cosmology

Posted on January 6, 2021 by Valeria Pettorino

Abstract

We present a new summary statistic for weak lensing observables, higher than second order, suitable for extracting non-Gaussian cosmological information and inferring cosmological parameters. We name this statistic the 'starlet ℓ1-norm' as it is computed via the sum of the absolute values of the starlet (wavelet) decomposition coefficients of a weak lensing map. In comparison to the state-of-the-art higher-order statistics -- weak lensing peak counts and minimum counts, or the combination of the two -- the ℓ1-norm provides a fast multi-scale calculation of the full void and peak distribution, avoiding the problem of defining what a peak is and what a void is: The ℓ1-norm carries the information encoded in all pixels of the map, not just the ones in local maxima and minima. We show its potential by applying it to the weak lensing convergence maps provided by the MassiveNus simulations to get constraints on the sum of neutrino masses, the matter density parameter, and the amplitude of the primordial power spectrum. We find that, in an ideal setting without further systematics, the starlet ℓ1-norm remarkably outperforms commonly used summary statistics, such as the power spectrum or the combination of peak and void counts, in terms of constraining power, representing a promising new unified framework to simultaneously account for the information encoded in peak counts and voids. We find that the starlet ℓ1-norm outperforms the power spectrum by 72% on Mν, 60% on Ωm, and 75% on As for the Euclid-like setting considered; it also improves upon the state-of-the-art combination of peaks and voids for a single smoothing scale by 24% on Mν, 50% on Ωm, and 24% on As.

Multi-CCD Point Spread Function Modelling

Posted on November 20, 2020July 6, 2022 by Tobias Liaudat

Context. Galaxy imaging surveys observe a vast number of objects that are affected by the instrument’s Point Spread Function (PSF). Weak lensing missions, in particular, aim at measuring the shape of galaxies, and PSF effects represent an important source of systematic errors which must be handled appropriately. This demands a high accuracy in the modelling as well as the estimation of the PSF at galaxy positions.

Aims. Sometimes referred to as non-parametric PSF estimation, the goal of this paper is to estimate a PSF at galaxy positions, starting from a set of noisy star image observations distributed over the focal plane. To accomplish this, we need our model to first of all, precisely capture the PSF field variations over the Field of View (FoV), and then to recover the PSF at the selected positions. Methods. This paper proposes a new method, coined MCCD (Multi-CCD PSF modelling), that creates, simultaneously, a PSF field model over all of the instrument’s focal plane. This allows to capture global as well as local PSF features through the use of two complementary models which enforce different spatial constraints. Most existing non-parametric models build one model per Charge-Coupled Device (CCD), which can lead to difficulties in capturing global ellipticity patterns.

Results. We first test our method on a realistic simulated dataset comparing it with two state-of-the-art PSF modelling methods (PSFEx and RCA). We outperform both of them with our proposed method. Then we contrast our approach with PSFEx on real data from CFIS (Canada-France Imaging Survey) that uses the CFHT (Canada-France-Hawaii Telescope). We show that our PSF model is less noisy and achieves a ~ 22% gain on pixel Root Mean Squared Error (RMSE) with respect to PSFEx.

Conclusions. We present, and share the code of, a new PSF modelling algorithm that models the PSF field on all the focal plane that is mature enough to handle real data.

Reference: Tobias Liaudat, Jérôme Bonnin, Jean-Luc Starck, Morgan A. Schmitz, Axel Guinot, Martin Kilbinger and Stephen D. J. Gwyn. “Multi-CCD Point Spread Function Modelling”, submitted 2020.

arXiv, code.

Probabilistic Mapping of Dark Matter by Neural Score Matching

Posted on November 19, 2020 by Benjamin Remy

The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but its presence can be inferred through the small gravitational lensing effect it has on the images of far away galaxies. By measuring this lensing effect on a large number of galaxies it is possible to reconstruct maps of the Dark Matter distribution on the sky. This, however, represents an extremely challenging inverse problem due to missing data and noise dominated measurements. In this work, we present a novel methodology for addressing such inverse problems by combining elements of Bayesian statistics, analytic physical theory, and a recent class of Deep Generative Models based on Neural Score Matching. This approach allows to do the following: (1) make full use of analytic cosmological theory to constrain the 2pt statistics of the solution, (2) learn from cosmological simulations any differences between this analytic prior and full simulations, and (3) obtain samples from the full Bayesian posterior of the problem for robust Uncertainty Quantification. We present an application of this methodology on the first deep-learning-assisted Dark Matter map reconstruction of the Hubble Space Telescope COSMOS field.

Reference: Benjamin Remy, François Lanusse, Zaccharie Ramzi, Jia Liu, Niall Jeffrey and Jean-Luc Starck. “Probabilistic Mapping of Dark Matter by Neural Score Matching”, Machine Learning and the Physical Sciences Workshop, NeurIPS 2020.

arXiv, code.

Euclid preparation: VII. Forecast validation for Euclid cosmological probes

Posted on October 20, 2020November 22, 2020 by Valeria Pettorino

Abstract

Aims: The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. The estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on various individual methodologies and numerical implementations, which were developed for different observational probes and for the combination thereof. In this paper we present validated forecasts, which combine both theoretical and observational ingredients for different cosmological probes. This work is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts.
Methods: We describe in detail the methods adopted for Fisher matrix forecasts, which were applied to galaxy clustering, weak lensing, and the combination thereof. We estimated the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations, some of which are made publicly available, in different programming languages, together with a reference training-set of input and output matrices for a set of specific models. These can be used by the reader to validate their own implementations if required.
Results: We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setting, for example flat or non-flat spatial cosmologies, or different cuts at non-linear scales. The numerical implementations are now reliable for these settings. We present the results for an optimistic and a pessimistic choice for these types of settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy figure of merit by at least a factor of three.

Euclid: The importance of galaxy clustering and weak lensing cross-correlations within the photometric Euclid survey

Posted on April 30, 2020November 22, 2020 by Valeria Pettorino

Authors:	Tutusaus, I.;Martinelli, M.;Cardone, V. F.;Camera, S.;Yahia-Cherif, S.;Casas, S.;Blanchard, A.;Kilbinger, M.;Lacasa, F.;Sakr, Z.;Ilić, S.;Kunz, M.;Carbone, C.;Castander, F. J.;Dournac, F.;Fosalba, P.;Kitching, T.;Markovic, K.;Mangilli, A.;Pettorino, V.;Sapone, D.;Yankelevich, V.;et al.
Journal:	Astronomy & Astrophysics, Volume 643, id.A70, 17 pp.
Year:	11/2020
Download:	Inspire\| Arxiv \| DOI

Abstract

Context. The data from the Euclid mission will enable the measurement of the angular positions and weak lensing shapes of over a billion galaxies, with their photometric redshifts obtained together with ground-based observations. This large dataset, with well-controlled systematic effects, will allow for cosmological analyses using the angular clustering of galaxies (GC_ph) and cosmic shear (WL). For Euclid, these two cosmological probes will not be independent because they will probe the same volume of the Universe. The cross-correlation (XC) between these probes can tighten constraints and is therefore important to quantify their impact for Euclid.
Aims: In this study, we therefore extend the recently published Euclid forecasts by carefully quantifying the impact of XC not only on the final parameter constraints for different cosmological models, but also on the nuisance parameters. In particular, we aim to decipher the amount of additional information that XC can provide for parameters encoding systematic effects, such as galaxy bias, intrinsic alignments (IAs), and knowledge of the redshift distributions.
Methods: We follow the Fisher matrix formalism and make use of previously validated codes. We also investigate a different galaxy bias model, which was obtained from the Flagship simulation, and additional photometric-redshift uncertainties; we also elucidate the impact of including the XC terms on constraining these latter.
Results: Starting with a baseline model, we show that the XC terms reduce the uncertainties on galaxy bias by ∼17% and the uncertainties on IA by a factor of about four. The XC terms also help in constraining the γ parameter for minimal modified gravity models. Concerning galaxy bias, we observe that the role of the XC terms on the final parameter constraints is qualitatively the same irrespective of the specific galaxy-bias model used. For IA, we show that the XC terms can help in distinguishing between different models, and that if IA terms are neglected then this can lead to significant biases on the cosmological parameters. Finally, we show that the XC terms can lead to a better determination of the mean of the photometric galaxy distributions.
Conclusions: We find that the XC between GC_ph and WL within the Euclid survey is necessary to extract the full information content from the data in future analyses. These terms help in better constraining the cosmological model, and also lead to a better understanding of the systematic effects that contaminate these probes. Furthermore, we find that XC significantly helps in constraining the mean of the photometric-redshift distributions, but, at the same time, it requires more precise knowledge of this mean with respect to single probes in order not to degrade the final "figure of merit".

Euclid: The reduced shear approximation and magnification bias for Stage IV cosmic shear experiments

Posted on April 27, 2020June 30, 2020 by Valeria Pettorino

Abstract

Stage IV weak lensing experiments will offer more than an order of magnitude leap in precision. We must therefore ensure that our analyses remain accurate in this new era. Accordingly, previously ignored systematic effects must be addressed. In this work, we evaluate the impact of the reduced shear approximation and magnification bias, on the information obtained from the angular power spectrum. To first-order, the statistics of reduced shear, a combination of shear and convergence, are taken to be equal to those of shear. However, this approximation can induce a bias in the cosmological parameters that can no longer be neglected. A separate bias arises from the statistics of shear being altered by the preferential selection of galaxies and the dilution of their surface densities, in high-magnification regions. The corrections for these systematic effects take similar forms, allowing them to be treated together. We calculated the impact of neglecting these effects on the cosmological parameters that would be determined from Euclid, using cosmic shear tomography. To do so, we employed the Fisher matrix formalism, and included the impact of the super-sample covariance. We also demonstrate how the reduced shear correction can be calculated using a lognormal field forward modelling approach. These effects cause significant biases in Omega_m, sigma_8, n_s, Omega_DE, w_0, and w_a of -0.53 sigma, 0.43 sigma, -0.34 sigma, 1.36 sigma, -0.68 sigma, and 1.21 sigma, respectively. We then show that these lensing biases interact with another systematic: the intrinsic alignment of galaxies. Accordingly, we develop the formalism for an intrinsic alignment-enhanced lensing bias correction. Applying this to Euclid, we find that the additional terms introduced by this correction are sub-dominant.

Authors:	E. Ayçoberry, V. Ajani, A. Guinot, M. Kilbinger, V. Pettorino, S. Farrens, J.-L. Starck, R. Gavazzi, M. Hudson
Journal:	A&A
Year:	2022
DOI:
Download:	ADS \| arXiv

Authors:	A. Guinot, M. Kilbinger, S. Farrens, A. Peel, A. Pujol, M. Schmitz, J.-L. Starck, T. Erben, R. Gavazzi, S. Gwyn, M. Hudson, H. Hiledebrandt, T. Liaudat , et. al
Journal:	A&A
Year:	2022
DOI:
Download:	ADS \| arXiv

Authors:	S. Farrens, A. Guinot, M. Kilbinger, T. Liaudat , L. Baumont, X. Jimenez, A. Peel , A. Pujol , M. Schmitz, J.-L. Starck, and A. Z. Vitorelli
Journal:	A&A
Year:	2022
DOI:	10.1051/0004-6361/202243970
Download:	ADS \| arXiv

Authors:	A.C. Deshpande, ..., S. Casas, M. Kilbinger, V. Pettorino, S. Pires, J.-L. Starck, F. Sureau, et al.
Journal:	Astronomy and Astrophysics
Year:	2020
DOI:	10.1051/0004-6361/201937323
Download:	ADS \| arXiv

Category: Weak Lensing Publications

UNIONS: The impact of systematic errors on weak-lensing peak counts

Abstract

ShapePipe: a new shape measurement pipeline and weak-lensing application to UNIONS/CFIS data

Abstract

ShapePipe: A modular weak-lensing processing and analysis pipeline

Abstract

Early dark energy in the pre- and post-recombination epochs

Early dark energy in the pre- and postrecombination epochs

Abstract

Starlet l1-norm for weak lensing cosmology

Starlet l1-norm for weak lensing cosmology

Abstract

Multi-CCD Point Spread Function Modelling

Probabilistic Mapping of Dark Matter by Neural Score Matching

Euclid preparation: VII. Forecast validation for Euclid cosmological probes

Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear

Abstract

Euclid: The importance of galaxy clustering and weak lensing cross-correlations within the photometric Euclid survey

Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear

Abstract

Euclid: The reduced shear approximation and magnification bias for Stage IV cosmic shear experiments

Euclid: The reduced shear approximation and magnification bias for Stage IV cosmic shear experiments

Abstract

Authors:	Adrià Gómez-Valent, Ziyang Zheng, Luca Amendola, Valeria Pettorino, Christof Wetterich
Journal:	PRD
Year:	07/2021
Download:	PRD \| Arxiv

Authors:	Virginia Ajani, Jean-Luc Starck, Valeria Pettorino
Journal:	Astronomy & Astrophysics , Forthcoming article, Letters to the Editor
Year:	01/2021
Download:	A&A\| Arxiv

Authors:	Euclid Collaboration;Blanchard, A.;Camera, S.;Carbone, C.;Cardone, V. F.;Casas, S.;Clesse, S.;Ilić, S.;Kilbinger, M.;Kitching, T.;Kunz, M.;Lacasa, F.;Linder, E.;Majerotto, E.;Markovič, K.;Martinelli, M.;Pettorino, V.;Pourtsidou, A.;Sakr, Z.;Sánchez, A. G.;Sapone, D.;Tutusaus, I.;Yahia-Cherif, S.;Yankelevich, V.;et al.
Journal:	Astronomy & Astrophysics, Volume 642, id.A191, 66 pp.
Year:	10/2020
Download:	Inspire\| Arxiv