Ray‐tracing Simulations of Weak Lensing by Large‐Scale Structure
Author(s) -
Bhuvnesh Jain,
Uroš Seljak,
Simon D. M. White
Publication year - 2000
Publication title -
the astrophysical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.376
H-Index - 489
eISSN - 1538-4357
pISSN - 0004-637X
DOI - 10.1086/308384
Subject(s) - weak gravitational lensing , spectral density , physics , gaussian , ray tracing (physics) , statistical physics , computational physics , nonlinear system , robustness (evolution) , sky , optics , galaxy , astrophysics , redshift , statistics , mathematics , biochemistry , chemistry , gene , quantum mechanics
We investigate weak lensing by large-scale structure using ray tracingthrough N-body simulations. Photon trajectories are followed through highresolution simulations of structure formation to make simulated maps of shearand convergence on the sky. Tests with varying numerical parameters are used tocalibrate the accuracy of computed lensing statistics on angular scales fromabout 1 arcminute to a few degrees. Various aspects of the weak lensingapproximation are also tested. For fields a few degrees on a side the shearpower spectrum is almost entirely in the nonlinear regime and agrees well withnonlinear analytical predictions. Sampling fluctuations in power spectrumestimates are investigated by comparing several ray tracing realizations of agiven model. For survey areas smaller than a degree on a side the main sourceof scatter is nonlinear coupling to modes larger than the survey. We develop amethod which uses this effect to estimate the mass density parameter Omega fromthe scatter in power spectrum estimates for subregions of a larger survey. Weshow that the power spectrum can be measured accurately from realisticallynoisy data on scales corresponding to 1-10 Mpc/h. Non-Gaussian features in theone point distribution function of the weak lensing convergence (reconstructedfrom the shear) are also sensitive to Omega. We suggest several techniques forestimating Omega in the presence of noise and compare their statistical power,robustness and simplicity. With realistic noise Omega can be determined towithin 0.1-0.2 from a deep survey of several square degrees.Comment: 59 pages, 22 figures included. Matches version accepted for Ap
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