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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.

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GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology

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.
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On Random Walks with a General Moving Barrier

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.
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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.
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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.
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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.