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The Accuracy of Weak Lensing Simulations

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arxiv 1910.10625 v2 pith:7EJV7KXU submitted 2019-10-23 astro-ph.CO

classification astro-ph.CO
keywords lensingcodesconvergencepowersimulationspectraaccuracyagreement
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abstract

We investigate the accuracy of weak lensing simulations by comparing the results of five independently developed lensing simulation codes run on the same input $N$-body simulation. Our comparison focuses on the lensing convergence maps produced by the codes, and in particular on the corresponding PDFs, power spectra and peak counts. We find that the convergence power spectra of the lensing codes agree to $\lesssim 2\%$ out to scales $\ell \approx 4000$. For lensing peak counts, the agreement is better than $5\%$ for peaks with signal-to-noise $\lesssim 6$. We also discuss the systematic errors due to the Born approximation, line-of-sight discretization, particle noise and smoothing. The lensing codes tested deal in markedly different ways with these effects, but they nonetheless display a satisfactory level of agreement. Our results thus suggest that systematic errors due to the operation of existing lensing codes should be small. Moreover their impact on the convergence power spectra for a lensing simulation can be predicted given its numerical details, which may then serve as a validation test.

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  1. Game of cones: A nulling strategy for modelling lensing convergence in cones with large deviation theory

    astro-ph.CO 2019-09 conditional novelty 6.0 of 10

    The one-point probability distribution of weak-lensing convergence is derived from large-deviation theory and validated against ray-tracing simulations, with a nulling technique restoring percent-level accuracy in the tails.

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