Speaker: Marcel Zemp (KIAA/PKU)  

　　Time: Thursday, 3:00pm, December 5th  

　　Location: Lecture Hall, 3rd floor 

　　Abstract: on practice to describe formal size and mass scales of dark matter haloes as spherical overdensities with respect to an evolving density threshold. We critically investigate the evolutionary effects of several such commonly used definitions and compare it to the evolution within fixed physical scales and of other intrinsic physical properties of dark matter haloes. We show that, in general, the traditional way of characterising sizes and masses of haloes dramatically overpredicts the degree of evolution in the last 10 Gyr, especially for low mass haloes. This pseudo-evolution is leading to the illusion of growth despite no major changes within fixed physical scales happening. Such formal size definitions also serve as proxies for the virialised region of a halo in the literature. In general, those spherical overdensity scales do not coincide with the virialised region though. We question the importance of the role of formal virial quantities currently ubiquitously used in descriptions, models and relations that involve properties of dark matter structures. Concepts and relations based on pseudo-evolving formal virial quantities are likely not of fundamental nature and can potentially lead to an inaccurate physical picture of the evolution of our Universe. 

　　Biog: Marcel Zemp studied physics at ETH Zurich, Switzerland, and got a doctorate in science degree (Dr. sc.) from ETH Zurich in 2006. Afterwards, he spend 5 years as a post-doctoral researcher in the USA. From 2006 to 2008 at University of California Santa Cruz and from 2008 to 2011 at University of Michigan at Ann Arbor. In September 2011, he joined the Kavli Institute for Astronomy and Astrophysics at Peking University as a Bairen Research Professor. His main interests are cosmological structure formation, galaxy formation, dynamics, dark matter, dark energy, cosmology in general, black holes, N-body techniques, integrators, algorithms, data analysis methods and visualisations.