Increasing the lensing figure of merit through higher order convergence moments

Vicinanza, Martina; Cardone, V. F.; Maoli, R.; Scaramella, R.; Er, Xinzhong

doi:10.1103/physrevd.97.023519

Cited by 25 publications

(22 citation statements)

References 67 publications

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“…non-Gaussian) summary statistics, and whether we understand, at the same level as the two-point statistics, the non-trivial systematic effects in these higher-order statistics. Common higher-order statistics with weak lensing include shear peak statistics (Dietrich & Hartlap 2010;Kratochvil et al 2010;Liu et al 2015;Kacprzak et al 2016;Martinet et al 2018;Peel et al 2018;Shan et al 2018;Ajani et al 2020), higher moments of the weak lensing convergence (Van Waerbeke et al 2013;Petri et al 2015;Vicinanza et al 2016;Chang et al 2018;Vicinanza et al 2018;Peel et al 2018;Gatti et al 2020b), three-point correlation functions or bispectra (Takada & Jain 2003Semboloni et al 2011;Fu et al 2014), Minkowski functionals (Kratochvil et al 2012;Petri et al 2015;Vicinanza et al 2019;Parroni et al 2020), and machine-learning methods (Ribli et al 2019;Fluri et al 2018Fluri et al , 2019Jeffrey et al 2021). Many of these have recently been applied to data (Liu et al 2015;Kacprzak et al 2016;Martinet et al 2018;Fluri et al 2019;Jeffrey et al 2021), often performing well in terms of cosmological constraints.…”

Section: Introductionmentioning

confidence: 99%

Dark Energy Survey Year 3 results: Curved-sky weak lensing mass map reconstruction

Jeffrey

Gatti

Chang

et al. 2021

Monthly Notices of the Royal Astronomical Society

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We present reconstructed convergence maps, mass maps, from the Dark Energy Survey (DES) third year (Y3) weak gravitational lensing data set. The mass maps are weighted projections of the density field (primarily dark matter) in the foreground of the observed galaxies. We use four reconstruction methods, each is a maximum a posteriori estimate with a different model for the prior probability of the map: Kaiser-Squires, null B-mode prior, Gaussian prior, and a sparsity prior. All methods are implemented on the celestial sphere to accommodate the large sky coverage of the DES Y3 data. We compare the methods using realistic ΛCDM simulations with mock data that are closely matched to the DES Y3 data. We quantify the performance of the methods at the map level and then apply the reconstruction methods to the DES Y3 data, performing tests for systematic error effects. The maps are compared with optical foreground cosmic-web structures and are used to evaluate the lensing signal from cosmic-void profiles. The recovered dark matter map covers the largest sky fraction of any galaxy weak lensing map to date.

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Section: Introductionmentioning

confidence: 99%

Dark Energy Survey Year 3 results: Curved-sky weak lensing mass map reconstruction

Jeffrey

Gatti

Chang

et al. 2021

Monthly Notices of the Royal Astronomical Society

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“…Two-point statistics fail to capture this non-Gaussian information and thus yield an incomplete description of the matter distribution at low redshift. To close this gap, the community has recently started to explore non-Gaussian cosmic shear estimators: for example weak-lensing peaks (e.g., Kruse & Schneider 1999, 2000Dietrich & Hartlap 2010;Kratochvil et al 2010;Fan et al 2010;Yang et al 2011;Maturi et al 2011;Hamana et al 2012;Hilbert et al 2012;Marian et al 2012Marian et al , 2013Shan et al 2014Shan et al , 2018Lin & Kilbinger 2015;Martinet et al 2015Martinet et al , 2018Liu et al 2015a,b;Kacprzak et al 2016;Petri et al 2016;Zorrilla Matilla et al 2016;Giocoli et al 2018;Peel et al 2018;Davies et al 2019;Fong et al 2019;Li et al 2019;Weiss et al 2019;Yuan et al 2019;Coulton et al 2020;Ajani et al 2020;Zürcher et al 2021), Minkowski functionals (e.g., Kratochvil et al 2012;Petri et al 2015;Vicinanza et al 2019;Parroni et al 2020;Zürcher et al 2021), higher-order moments (e.g., Van Waerbeke et al 2013;Petri et al 2015;Peel et al 2018;Vicinanza et al 2018;…”

Section: Introductionmentioning

confidence: 99%

Probing dark energy with tomographic weak-lensing aperture mass statistics

Martinet

Harnois-Déraps

Jullo

et al. 2021

A&A

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We forecast and optimize the cosmological power of various weak-lensing aperture mass (Map) map statistics for future cosmic shear surveys, including peaks, voids, and the full distribution of pixels (1D Map). These alternative methods probe the non-Gaussian regime of the matter distribution, adding complementary cosmological information to the classical two-point estimators. Based on the SLICS and cosmo-SLICS N-body simulations, we build Euclid-like mocks to explore the S8 − Ωm − w0 parameter space. We develop a new tomographic formalism that exploits the cross-information between redshift slices (cross-Map) in addition to the information from individual slices (auto-Map) probed in the standard approach. Our auto-Map forecast precision is in good agreement with the recent literature on weak-lensing peak statistics and is improved by ∼50% when including cross-Map. It is further boosted by the use of 1D Map that outperforms all other estimators, including the shear two-point correlation function (γ-2PCF). When considering all tomographic terms, our uncertainty range on the structure growth parameter S8 is enhanced by ∼45% (almost twice better) when combining 1D Map and the γ-2PCF compared to the γ-2PCF alone. We additionally measure the first combined forecasts on the dark energy equation of state w0, finding a factor of three reduction in the statistical error compared to the γ-2PCF alone. This demonstrates that the complementary cosmological information explored by non-Gaussian Map map statistics not only offers the potential to improve the constraints on the recent σ8–Ωm tension, but also constitutes an avenue to understanding the accelerated expansion of our Universe.

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“…Recent studies have shown that combining the shear twopoint statistics with higher-order statistics of the convergence such as higher-order moments (Vicinanza et al 2018), Minkowski functionals (Vicinanza et al 2019), or peak counts (Liu et al 2015;Martinet et al 2018) allows breaking common degeneracies. The precision of the KS+ mass inversion makes the E-mode convergence maps a promising tool for such cosmological studies.…”

Section: Resultsmentioning

confidence: 99%

Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies

Pires

Vandenbussche

Kansal

et al. 2020

A&A

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Weak lensing, which is the deflection of light by matter along the line of sight, has proven to be an efficient method for constraining models of structure formation and reveal the nature of dark energy. So far, most weak-lensing studies have focused on the shear field that can be measured directly from the ellipticity of background galaxies. However, within the context of forthcoming full-sky weak-lensing surveys such as Euclid, convergence maps (mass maps) offer an important advantage over shear fields in terms of cosmological exploitation. While it carry the same information, the lensing signal is more compressed in the convergence maps than in the shear field. This simplifies otherwise computationally expensive analyses, for instance, non-Gaussianity studies. However, the inversion of the non-local shear field requires accurate control of systematic effects caused by holes in the data field, field borders, shape noise, and the fact that the shear is not a direct observable (reduced shear). We present the two mass-inversion methods that are included in the official Euclid data-processing pipeline: the standard Kaiser & Squires method (KS), and a new mass-inversion method (KS+) that aims to reduce the information loss during the mass inversion. This new method is based on the KS method and includes corrections for mass-mapping systematic effects. The results of the KS+ method are compared to the original implementation of the KS method in its simplest form, using the Euclid Flagship mock galaxy catalogue. In particular, we estimate the quality of the reconstruction by comparing the two-point correlation functions and third- and fourth-order moments obtained from shear and convergence maps, and we analyse each systematic effect independently and simultaneously. We show that the KS+ method substantially reduces the errors on the two-point correlation function and moments compared to the KS method. In particular, we show that the errors introduced by the mass inversion on the two-point correlation of the convergence maps are reduced by a factor of about 5, while the errors on the third- and fourth-order moments are reduced by factors of about 2 and 10, respectively.

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Increasing the lensing figure of merit through higher order convergence moments

Cited by 25 publications

References 67 publications

Dark Energy Survey Year 3 results: Curved-sky weak lensing mass map reconstruction

Dark Energy Survey Year 3 results: Curved-sky weak lensing mass map reconstruction

Probing dark energy with tomographic weak-lensing aperture mass statistics

Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies

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