activity
20122026
most citedNon-local Lagrangian bias

103 citations · 145 across the 3 of their papers we have counts for

collaborators
Showing astro-ph.COShow all

7 papers · 1 filter

astro-ph.CO2026

Radial velocity statistics of cosmic voids as a probe of interacting dark energy

Kin Ho Luo, Ming-chung Chu, Kwan Chuen Chan +1

Due to their vast sizes and extremely low densities, the dynamics of cosmic voids are largely decoupled from complex, small-scale baryonic physics and are highly sensitive to the b…

astro-ph.CO2018

Constraint of Void Bias on Primordial non-Gaussianity

Kwan Chuen Chan, Nico Hamaus, Matteo Biagetti

We study the large-scale bias parameter of cosmic voids with primordial non-Gaussian (PNG) initial conditions of the local type. In this scenario, the dark matter halo bias exhibit…

astro-ph.CO2017

Bispectrum Supersample Covariance

Kwan Chuen Chan, Azadeh Moradinezhad Dizgah, Jorge Noreña

Modes with wavelengths larger than the survey window can have significant impact on the covariance within the survey window. The supersample covariance has been recognized as an im…

astro-ph.CO2017★ 42 cited

Shot noise and biased tracers: a new look at the halo model

Dimitry Ginzburg, Vincent Desjacques, Kwan Chuen Chan

Shot noise is an important ingredient to any measurement or theoretical modeling of discrete tracers of the large scale structure. Recent work has shown that the shot noise in the…

astro-ph.CO2017

Consistency relations for the Lagrangian halo bias and their implications

Kwan Chuen Chan, Ravi K. Sheth, Roman Scoccimarro

The protohalo patches from which halos form are defined by a number of constraints imposed on the Lagrangian dark matter density field. Each of these constraints contributes to bia…

astro-ph.CO2016

Assessment of the Information Content of the Power Spectrum and Bispectrum

Kwan Chuen Chan, Linda Blot

The covariance matrix of the matter and halo power spectrum and bispectrum are studied. Using a large suite of simulations, we find that the non-Gaussianity in the covariance is si…