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Probing the gravity-induced bias with weak lensing: test of analytical results against simulations

2000/01/13 by D. Munshi, Dipak Munshi
Physics and Astronomy · #Ansatz #Astronomy and Astrophysical Research #Astrophysics #Cluster analysis #Convergence (economics) #Cosmology #Cosmology and Gravitation Theories #Field (mathematics) #Galaxies: Formation, Evolution, Phenomena #Galaxy #Gravitational lensing formalism #Physics #Quantum mechanics #Redshift #Smoothing #Statistical physics #Statistics #Weak gravitational lensing #astro-ph

paper · pdf · doi:10.1046/j.1365-8711.2000.03707.x

published as Mon.Not.Roy.Astron.Soc.318:145,2000 · 17 pages including 8 figures and 1 table, MNRAS, submitted

arxiv created 2000/01/13 · openalex publication_date 2000/10/11 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Future weak lensing surveys will directly probe the density fluctuation in the Universe. Recent studies have shown how the statistics of the weak lensing convergence field is related to the statistics of collapsed objects. Extending earlier analytical results on the probability distribution function of the convergence field, we show that the bias associated with the convergence field can be directly related to the bias associated with the statistics of underlying overdense objects. This will provide us with a direct method to study the gravity-induced bias in galaxy clustering. Based on our analytical results, which use the hierarchical Ansatz for non-linear clustering, we study how such a bias depends on the smoothing angle and the source redshift. We compare our analytical results with ray-tracing experiments through N-body simulations of four different realistic cosmological scenarios, and find a very good match. Our study shows that the bias in the convergence map strongly depends on the background geometry and hence can help us in distinguishing different cosmological models in addition to improving our understanding of the gravity-induced bias in galaxy clustering.

Citations