2 papers
astro-ph.GA2024
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…
astro-ph.CO2024
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…