摘要

Weak lensing (WL) effects arise from the gravitational light deflection by large-scale structures, and thus are powerful tools to probe the nature of the dark universe. Their signals are dominantly from relatively small-scale nonlinear structures, and therefore possess significant non-Gaussianity. Statistical analyses of WL effects thus need to be multi approaches. In this presentation, motivated by the recent machine learning results, I will talk about the use of WL steepness as a cosmological probe by presenting our theoretical model and the comparisons with numerical simulations. The applicability of WL steepness statistics will also be discussed.

报告人简介

 Zuhui Fan received her Ph.D. in 1995 from University of Washington in Seattle, U.S.A..  From 1996 to 2002, she was a visiting scientist and a postdoc fellow in University of Chicago and Taiwan University/ASIAA, Taiwan, respectively. From 2002 to 2018, she was a professor at Department of Astronomy, School of Physics, Peking University. In Nov. 2018, she moved to the South-Western Institute for Astronomy Research at Yunnan University. She is now a professor there. Her research interest is in cosmology, particularly in weak lensing cosmological studies in the recent years.