Improving PSF modelling for weak gravitational lensing using new methods in model selection
Barnaby Rowe

TL;DR
This paper introduces a new theoretical framework and diagnostic tools for better model selection in PSF modeling for weak gravitational lensing, enhancing the accuracy of cosmic shear measurements.
Contribution
It presents a novel set of correlation-based diagnostics for PSF model residuals, improving model selection in weak lensing data analysis.
Findings
Diagnostic functions effectively identify suitable models for PSF residuals.
Simulations show improved model selection accuracy with the new diagnostics.
The approach can complement existing model selection criteria like AIC and BIC.
Abstract
A simple theoretical framework for the description and interpretation of spatially correlated modelling residuals is presented, and the resulting tools are found to provide a useful aid to model selection in the context of weak gravitational lensing. The description is focused upon the specific problem of modelling the spatial variation of a telescope point spread function (PSF) across the instrument field of view, a crucial stage in lensing data analysis, but the technique may be used to rank competing models wherever data are described empirically. As such it may, with further development, provide useful extra information when used in combination with existing model selection techniques such as the Akaike and Bayesian Information Criteria, or the Bayesian evidence. Two independent diagnostic correlation functions are described and the interpretation of these functions demonstrated…
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