学术报告
学术报告
Large-scale Clustering of the Underdense Regions
admin 645 阅读 2020-10-17

报告人:Associate professor Kwan Chuen Chan,SUN YAT-SEN UNIVERSITY

开始日期:2020-10-19

开始时间:2020-10-19 14:00~15:00

活动地点:天文系会议室508

活动介绍
Abstract

Current large-scale structure surveys mostly focus on the overdesne regions of the universe. However, the dominant regions in the large-scale structure are of low density compared to the mean value and the clustering of the underdense regions may have information complementary to that of the halo clustering. Comsic voids are large underdense regions in the large-scale structure. In this this talk I will discuss the clustering of voids, especially their linear bias, quadratic bias, and the void bias in the primordial non-Gaussianity scenario. In the second part of the talk, I introduce the volume statistics as a probe of the distribution of the underdense regions. Compared to voids, this statistic is less sensitive to the shot noise contaminations and could be easier to model. Using simulations, the bias of the volume statistics is meansured and determined to be negative. The Baryon Acoustic Oscillations are also measured and there is no systematic shift in the position.

Biography
Kwan Chuen Chan is currently an associate professor at Sun-Yat Sen University. He finished PhD at New York University in 2012. After graduation, he did postdoc research at University of Geneva (2012-2015) and Institute of Space Sciences in Barcelona (2015-2017). He joined the Sun-Yat Sen University as faculty since 2017.  He mainly works on the theory and simulation of the large-scale structure of the universe. Besides he also contributes significantly to the measurement of the BAO in the dark energy Survey. 
负责分部
天文与天体物理

版权所有:Copyright © PAC (2020).上海交通大学粒子天体物理与宇宙学教育部重点实验室

联系地址:上海市东川路800号李政道图书馆4楼

联系电话:021-54743772 E-mail:hyzhao@sjtu.edu.cn 邮编:200240 ICP备案编号:沪交ICP备20200311