295 citations · 1.5k across the 38 of their papers we have counts for
5 papers · 1 filter
Galaxies on graph neural networks: towards robust synthetic galaxy catalogs with deep generative models
Yesukhei Jagvaral, Francois Lanusse, Sukhdeep Singh +3
The future astronomical imaging surveys are set to provide precise constraints on cosmological parameters, such as dark energy. However, production of synthetic data for these surv…
RSD measurements from BOSS galaxy power spectrum using the halo perturbation theory model
Byeonghee Yu, Uros Seljak, Yin Li +1
We present growth of structure constraints from the cosmological analysis of the power spectrum multipoles of SDSS-III BOSS DR12 galaxies. We use the galaxy power spectrum model of…
Snowmass2021 Cosmic Frontier White Paper: Enabling Flagship Dark Energy Experiments to Reach their Full Potential
Jonathan A. Blazek, Doug Clowe, Thomas E. Collett +25
A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data…
Galaxies and Halos on Graph Neural Networks: Deep Generative Modeling Scalar and Vector Quantities for Intrinsic Alignment
Yesukhei Jagvaral, François Lanusse, Sukhdeep Singh +3
In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency…
Intrinsic alignments of bulges and discs
Yesukhei Jagvaral, Sukhdeep Singh, Rachel Mandelbaum
Galaxies exhibit coherent alignments with local structure in the Universe. This effect, called Intrinsic Alignments (IA), is an important contributor to the systematic uncertaintie…