Scintillation Timescales of Bright FRBs Detected by CHIME/FRB

Kavli Affiliate: Kiyoshi Masui | First 5 Authors: Eve Schoen, Calvin Leung, Kiyoshi Masui, Daniele Michilli, Pragya Chawla | Summary: We describe a pipeline to measure scintillation in fast radio bursts (FRBs) detected by CHIME/FRB in the 400-800 MHz band by analyzing the frequency structure of the FRB’s spectrum. We use the pipeline to measure […]


Continue.. Scintillation Timescales of Bright FRBs Detected by CHIME/FRB

Galaxy shapes of Light (GaLight): a 2D modeling of galaxy images

Kavli Affiliate: John D. Silverman | First 5 Authors: Xuheng Ding, Simon Birrer, Tommaso Treu, John D. Silverman, | Summary: Galight is a Python-based open-source package that can be used to perform two-dimensional model fitting of optical and near-infrared images to characterize the light distribution of galaxies with components including a disk, bulge, bar, and […]


Continue.. Galaxy shapes of Light (GaLight): a 2D modeling of galaxy images

Early-type galaxy density profiles from IllustrisTNG: III. Effects on outer kinematic structure

Kavli Affiliate: Risa Wechsler | First 5 Authors: Yunchong Wang, Shude Mao, Mark Vogelsberger, Volker Springel, Lars Hernquist | Summary: Early-type galaxies (ETGs) possess total radial density profiles that are largely described by singular isothermal spheres, which can lead to non-Gaussian line-of-sight velocity dispersion (LOSVD) under anisotropic stellar orbits. However, recent observations of local ETGs […]


Continue.. Early-type galaxy density profiles from IllustrisTNG: III. Effects on outer kinematic structure

Inferring halo masses with Graph Neural Networks

Kavli Affiliate: David N. Spergel | First 5 Authors: Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, Federico Marinacci | Summary: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work we build a model that infers the mass of a halo […]


Continue.. Inferring halo masses with Graph Neural Networks

Large deviation principle for stochastic generalized Ginzburg-Landau equation driven by jump noise

Kavli Affiliate: Ran Wang | First 5 Authors: Ran Wang, Beibei Zhang, , , | Summary: In this paper, we establish a large deviation principle for the stochastic generalized Ginzburg-Landau equation driven by jump noise. The main difficulties come from the highly non-linear coefficient. Here we adopt a new sufficient condition for the weak convergence […]


Continue.. Large deviation principle for stochastic generalized Ginzburg-Landau equation driven by jump noise