J
Jun Zhang
Researcher at Shanghai Jiao Tong University
Publications - 77
Citations - 1287
Jun Zhang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Weak gravitational lensing & Galaxy. The author has an hindex of 19, co-authored 71 publications receiving 1074 citations. Previous affiliations of Jun Zhang include Fermilab & University of California, Berkeley.
Papers
More filters
Journal ArticleDOI
GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology
Rachel Mandelbaum,Barnaby Rowe,Robert Armstrong,D. J. Bard,Emmanuel Bertin,James Bosch,D. Boutigny,Frederic Courbin,William A. Dawson,Annamaria Donnarumma,Ian Fenech Conti,Raphael Gavazzi,Marc Gentile,M. S. S. Gill,David W. Hogg,E. M. Huff,M. James Jee,Tomasz Kacprzak,Tomasz Kacprzak,Martin Kilbinger,T. Kuntzer,Dustin Lang,Wentao Luo,M. March,Philip J. Marshall,Joshua Meyers,Lance Miller,Hironao Miyatake,Hironao Miyatake,R. Nakajima,Fred Maurice Ngolè Mboula,Guldariya Nurbaeva,Yuki Okura,Stephane Paulin-Henriksson,Jason Rhodes,Michael Schneider,Huanyuan Shan,Erin Sheldon,Melanie Simet,Jean-Luc Starck,Florent Sureau,M. Tewes,Kristian Zarb Adami,Kristian Zarb Adami,Jun Zhang,Joe Zuntz +45 more
TL;DR: The recent GRavitational lEnsing Accuracy Testing (GREAT3) challenge as discussed by the authors was the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images.
Journal ArticleDOI
On Random Walks with a General Moving Barrier
Jun Zhang,Lam Hui +1 more
TL;DR: In this paper, the first-crossing distribution of random walks with a moving barrier of arbitrary shape is derived, which can satisfy an integral equation that can be solved by a simple matrix inversion, without the need for Monte Carlo simulations.
Journal ArticleDOI
Isolating Geometry in Weak-Lensing Measurements
TL;DR: In this article, the authors proposed a geometrical approach to constrain dark energy properties, free of any assumptions about the galaxy-mass/mass power spectrum (its shape, amplitude, or growth), which can yield a ~(0.03-0.07)f measurement on the dark energy abundance and equation of state.
Journal ArticleDOI
How to grow a healthy merger tree
TL;DR: In this article, seven Monte Carlo algorithms are compared for constructing merger histories of dark matter haloes, using the extended Press-Schechter (EPS) formalism based on both the spherical and ellipsoidal collapse models, and only the method of Kauffmann & White produces a progenitor mass function that is consistent with the EPS prediction for all look-back redshifts.
Journal ArticleDOI
The Bias and Mass Function of Dark Matter Halos in Non-Markovian Extension of the Excursion Set Theory
TL;DR: In this article, the authors derived an analytic expression for the halo bias in a new theoretical model that incorporates non-Markovian extension of the excursion set theory with a stochastic barrier.