13 citations · 40 across the 10 of their papers we have counts for
10 papers
Geometric deep learning for galaxy-halo connection: a case study for galaxy intrinsic alignments
Yesukhei Jagvaral, Francois Lanusse, Rachel Mandelbaum
Forthcoming cosmological imaging surveys, such as the Rubin Observatory LSST, require large-scale simulations encompassing realistic galaxy populations for a variety of scientific…
Unified framework for diffusion generative models in SO(3): applications in computer vision and astrophysics
Yesukhei Jagvaral, Francois Lanusse, Rachel Mandelbaum
Diffusion-based generative models represent the current state-of-the-art for image generation. However, standard diffusion models are based on Euclidean geometry and do not transla…
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…
Increasing the power of weak lensing survey data with multipole-based intrinsic alignment estimators
Sukhdeep Singh, Ali Shakir, Yesukhei Jagvaral +1
It has long been known that galaxy shapes align coherently with the large-scale density field. Characterizing this effect is essential to interpreting measurements of weak gravitat…
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…
Modeling halo and central galaxy orientations on the SO(3) manifold with score-based generative models
Yesukhei Jagvaral, Rachel Mandelbaum, Francois Lanusse
Upcoming cosmological weak lensing surveys are expected to constrain cosmological parameters with unprecedented precision. In preparation for these surveys, large simulations with…
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…
Probabilistic model for dynamic galaxy decomposition
Yesukhei Jagvaral, Duncan Campbell, Rachel Mandelbaum +1
In the era of precision cosmology and ever-improving cosmological simulations, a better understanding of different galaxy components such as bulges and discs will give us new insig…
Relativistic Lee Model and its Resolvent Analysis
Yesukhei Jagvaral, O. Teoman Turgut, Meltem Ünel
We reexamine the relativistic 2+1 dimensional Lee model in light-front coordinates on flat space and on a space-time with a spatial section given by a compact manifold in the usual…