295 citations · 1.5k across the 38 of their papers we have counts for
5 papers · 1 filter
Reinterpreting Fundamental Plane Correlations with Machine Learning
Chad Schafer, Sukhdeep Singh, Yesukhei Jagvaral
This work explores the relationships between galaxy sizes and related observable galaxy properties in a large volume cosmological hydrodynamical simulation. The objectives of this…
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…
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…
How Accurately Can We Detect the Splashback Radius of Dark Matter Halos and its Correlation With Accretion Rate?
Enia Xhakaj, Benedikt Diemer, Alexie Leauthaud +5
The splashback radius () of dark matter halos has recently been detected using weak gravitational lensing and cross-correlations with galaxies. However, different metho…