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Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables

机译:Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables

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摘要

We performed a series of numerical experiments to quantify the sensitivity of the predictions for weak lensing statistics obtained in ray-tracing dark matter (DM)-only simulations, to two hyper-parameters that influence the accuracy as well as the computational cost of the predictions: the thickness of the lens planes used to build past light cones and the mass resolution of the underlying DM simulation. The statistics considered are the power spectrum (PS) and a series of non-Gaussian observables, including the one-point probability density function, lensing peaks, and Minkowski functionals. Counterintuitively, we find that using thin lens planes (< 60 h~(-1) Mpc on a 240 h~(-1) Mpc simulation box) suppresses the PS over a broad range of scales beyond what would be acceptable for a survey comparable to the Large Synoptic Survey Telescope (LSST). A mass resolution of 7.2 × 10~(11) h~(-1) M_⊙ per DM particle (or 256~3 particles in a (240 h~(-1) Mpc)~3 box) is sufficient to extract information using the PS and non-Gaussian statistics from weak lensing data at angular scales down to 1′ with LSST-like levels of shape noise.

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