GalaxyFlow: Upsampling Hydrodynamical Simulations for Realistic Gaia Mock Catalogs by Sung Hak Lim et al. on Wednesday 23 November

Cosmological N-body simulations of galaxies operate at the level of "star

particles" with a mass resolution on the scale of thousands of solar masses.

Turning these simulations into stellar mock catalogs requires "upsampling" the

star particles into individual stars following the same phase-space density. In

this paper, we demonstrate that normalizing flows provide a viable upsampling

method that greatly improves on conventionally-used kernel smoothing algorithms

such as EnBiD. We demonstrate our flow-based upsampling technique, dubbed

GalaxyFlow, on a neighborhood of the Solar location in two simulated galaxies:

Auriga 6 and h277. By eye, GalaxyFlow produces stellar distributions that are

smoother than EnBiD-based methods and more closely match the Gaia DR3 catalog.

For a quantitative comparison of generative model performance, we introduce a

novel multi-model classifier test. Using this classifier test, we show that

GalaxyFlow more accurately estimates the density of the underlying star

particles than previous methods.

arXiv: http://arxiv.org/abs/http://arxiv.org/abs/2211.11765v1