arXiv subjects

Ulrich Steinwandel

Publications and source records attributed to Ulrich Steinwandel.

4 recordsLinked to original sources

arXiv2026

Learning the Universe with PRFM-vol: Introducing a new subgrid model for star formation in cosmological simulations

We introduce PRFM-vol, a new subgrid model for star formation in cosmological simulations that aims to increase the physical realism of cosmological simulations by leveraging results obtained with focused ISM simulations. We deploy a modified effective equation of state and calculate the star formation rate for each gas cell as a function of the ambient densities of gas, dark matter, and stars, based on the pressure-regulated feedback-modulated (PRFM) theory of star formation. Test simulations of our model in isolated galaxies show that we match PRFM predictions and TIGRESS scaling relations remarkably well, provided sufficiently high resolution is available. In particular, we are able to clearly demonstrate the impact of the stellar potential on the star formation rate, thereby retaining an important prediction of PRFM. We then apply our new model to cosmological multizoom simulations and find, compared to our previous TIGRESS/Schmidt model, a significant increase in the stellar scale heights and a slight increase in stellar mass. We demonstrate that modifying the effective equation of state significantly affects the morphology of simulated galaxies. Pronounced stellar clumps appear if the effective pressure at low hydrogen number densities is low, and disappear for higher pressure. We show that the formation of clumps is a result of Toomre instabilities, and conclude that simulated galaxy morphologies can be used to constrain effective equation of state models. Overall, our results establish PRFM-vol as a new self-consistent, physics-motivated subgrid model for star formation in high-resolution cosmological simulations.

astro-ph.GA↗

arXiv2022

Virgo: Scalable Unsupervised Classification of Cosmological Shock Waves

Cosmological shock waves are essential to understanding the formation of cosmological structures. To study them, scientists run computationally expensive high-resolution 3D hydrodynamic simulations. Interpreting the simulation results is challenging because the resulting data sets are enormous, and the shock wave surfaces are hard to separate and classify due to their complex morphologies and multiple shock fronts intersecting. We introduce a novel pipeline, Virgo, combining physical motivation, scalability, and probabilistic robustness to tackle this unsolved unsupervised classification problem. To this end, we employ kernel principal component analysis with low-rank matrix approximations to denoise data sets of shocked particles and create labeled subsets. We perform supervised classification to recover full data resolution with stochastic variational deep kernel learning. We evaluate on three state-of-the-art data sets with varying complexity and achieve good results. The proposed pipeline runs automatically, has only a few hyperparameters, and performs well on all tested data sets. Our results are promising for large-scale applications, and we highlight now enabled future scientific work.

astro-ph.IM↗

arXiv2019

WVTICs -- SPH initial conditions for everyone

We present a novel and fast application to generate glass-like initial conditions for Lagrangian hydrodynamic schemes (e.g. Smoothed Particle Hydrodynamics (SPH)) following arbitrary density models based on weighted Voronoi tessellations and combine it with improved initial configurations and an additional particle reshuffling scheme. We show our application's ability to sample different kinds of density features and to converge properly towards the given model density as well as a glass-like particle configuration. We analyse convergence with iterations as well as with varying particle number. Additionally, we demonstrate the versatility of the implemented algorithms by providing an extensive test suite for standard (magneto-) hydrodynamic test cases as well as a few common astrophysical applications. We indicate the potential to bridge further between observational astronomy and simulations as well as applicability to other fields of science by advanced features such as describing a density model using gridded data for exampling from an image file instead of an analytic model.

astro-ph.IM↗

arXiv2019

The Outer Stellar Halos of Galaxies: how Radial Merger Mass Deposition, Shells and Streams depend on Infall-Orbit Configurations

Galaxy mergers are a fundamental part of galaxy evolution. To study the resulting mass distributions of different kinds of galaxy mergers, we present a simulation suite of 36 high-resolution isolated merger simulations, exploring a wide range of parameter space in terms of mass ratios (mu = 1:5, 1:10, 1:50, 1:100) and orbital parameters. We find that mini mergers deposit a higher fraction of their mass in the outer halo compared to minor mergers, while their contribution to the central mass distribution is highly dependent on the orbital impact parameter: for larger pericentric distances we find that the centre of the host galaxy is almost not contaminated by merger particles. We also find that the median of the resulting radial mass distribution for mini mergers differs significantly from the predictions of simple theoretical tidal-force models. Furthermore, we find that mini mergers can increase the size of the host disc significantly without changing the global shape of the galaxy, if the impact occurs in the disc plane, thus providing a possible explanation for extended low-surface brightness disks reported in observations. Finally, we find clear evidence that streams are a strong indication of nearly circular infall of a satellite (with large angular momentum), whereas the appearance of shells clearly points to (nearly) radial satellite infall.

astro-ph.GA↗