A revised density split statistic model for general filters
Pierre Burger, Oliver Friedrich, Joachim Harnois-D\'eraps, and Peter, Schneider

TL;DR
This paper extends the density split statistics model for weak lensing to include a broad class of angular filters, improving the analysis of large-scale structure and cosmological parameter constraints.
Contribution
The authors generalize the DSS model to accommodate various filter functions, validated against simulations, enhancing its applicability for current and future weak lensing surveys.
Findings
The revised model fits simulation data with small systematic offsets.
Constraints from the model are comparable to two-point shear measures.
Model accuracy varies with filter type and size.
Abstract
Studying the statistical properties of the large-scale structure in the Universe with weak gravitational lensing is a prime goal of several current and forthcoming galaxy surveys. The power that weak lensing has to constrain cosmological parameters can be enhanced by considering statistics beyond second-order shear correlation functions or power spectra. One such higher-order probe that has proven successful in observational data is the density split statistics (DSS), in which one analyses the mean shear profiles around points that are classified according to their foreground galaxy density. In this paper, we generalise the most accurate DSS model to allow for a broad class of angular filter functions used for the classification of the different local density regions. This approach is motivated by earlier findings showing that an optimised filter can provide tighter constraints on model…
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