Fast estimation of aperture-mass statistics I: aperture mass variance and an application to the CFHTLenS data
Lucas Porth, Robert E. Smith, Patrick Simon, Laura Marian, Stefan, Hilbert

TL;DR
This paper introduces a fast, linear-order method for estimating aperture mass variance in weak lensing data, validated with simulations and applied to CFHTLenS, enabling efficient cosmological analysis.
Contribution
The paper presents a novel linear-order estimator for aperture mass statistics that is faster and more efficient than traditional methods, suitable for real survey data with masks.
Findings
The method accurately recovers known results from CFHTLenS data.
Inverse variance weighting improves aperture estimate accuracy.
Modest loss of cosmological information when excluding low completeness apertures.
Abstract
We explore an alternative method to the usual shear correlation function approach for the estimation of aperture mass statistics in weak lensing survey data. Our approach builds on the direct estimator method of Schneider (1998). In this paper, to test and validate the methodology, we focus on the aperture mass dispersion. After computing the signal and noise for a weighted set of measured ellipticites we show how the direct estimator can be made into a linear order algorithm that enables a fast and efficient computation. We then investigate the applicability of the direct estimator approach in the presence of a real survey mask with holes and chip gaps. For this we use a large ensemble of full ray-tracing mock simulations. By using various weighting schemes for combining information from different apertures we find that inverse variance weighting the individual aperture estimates with…
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