The design and precise implementation of joint-probe analyses are important research directions for large-scale structure surveys, such as DES (Dark Energy Survey) and LSST. The combination of galaxy clustering and weak lensing in DES has led to accurate measurement of dark energy and structure growth in the low-redshift universe. In this talk, I will focus on several systematic effects both on large scales and small scales, the covariances of joint-probes, as well as the computational challenges. I will explain how the FFTLog algorithm and its extensions overcome the challenges and enable accurate modeling for the joint-probe analyses. Accurate and efficient modeling methods like these will be in high demand in the future, when more probes and surveys are jointly analyzed to improve their scientific gains.
Dr. Xiao Fang is from University of Arizona. Xiao got his PhD from Ohio State University in 2018 working with Chris Hirata, and is currently a postdoc at Department of Astronomy and Steward Observatory, University of Arizona.
Meeting ID: 523 477 035
Joining Link:https://zoom.com.cn/j/523477035
The video record for today's talk is available below:
https://vshare.sjtu.edu.cn/play/45502b7bda8c34e4e65ac9f4daff333f
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