Rainer Weinberger

Diffuse gas in and around galaxies  can exist in a multi-phase state: cold gas clouds embedded in a hotter, volume filling medium. I am particularly interested in ways to model these states in computer simulations of galaxy formation without spatially resolving the clouds.

Starting out with initial state in the early universe, I am interested in the physical processes needed to reproduce observed present-day galaxies. We perform large-scale computer simulations to make these predictions.

How do collimated, energetic outflows driven by black holes in the center of galaxy clusters affect the intra-cluster gas and ultimately the rate of star formation in the central cluster galaxy

Over the past decade, advancements have enabled the simulation of galaxy formation starting from cosmological initial conditions. Simultaneously, cosmological surveys have achieved percent-level accuracy in model fitting. However, many traditional modelling approaches either overlook or greatly simplify the complex astrophysical processes that govern galaxy formation. This creates challenges for cosmology, particularly at ‘small-scale’ regimes where galaxy formation significantly influences cosmic structure. As part of the Learning the Universe collaboration, I am working with a team to address this challenge by jointly modeling cosmic structure and galaxy formation. Together, we are developing innovative methods to integrate essential galaxy formation processes into cosmological inference pipelines. 

In the nearby universe, massive galaxies are typically found in a quiescent state, characterized by low rates of star formation and predominantly old stellar populations. The transition to this phase, known as quenching, occurred roughly 10 billion years ago—at redshift 2 to 3—during an era commonly referred to as cosmic noon. To better understand the quenching process, we conducted a series of JWST NIRSpec observations on a representative sample of galaxies from this epoch, with the goal of investigating their gaseous and stellar properties. By creating numerical models that align with these observations, we are able to gain valuable insights into the conditions of these galaxies 10 billion years ago, as well as explore plausible mechanisms behind quenching, such as the influence of highly energetic active galactic nuclei. 

A common challenge in computational science is addressing multi-scale phenomena: large-scale environments influence small-scale behaviors, which in turn affect the larger system through complex feedback mechanisms. For instance, in galaxy formation, gas accreting into galactic centers powers an active galactic nucleus, resulting in significant reduction of star formation throughout the host galaxy over hundreds of millions of years. Similar multi-scale dynamics are present in climate models, where local phenomena impact global behavior, as well as in numerous other scientific and engineering fields. I am involved with Leibniz-Campus SCALES, an initiative that unites scientists modeling these phenomena in astrophysics, climate science, earth system modeling, and mathematicians focused on the underlying methodologies. Our goal is to learn from advances across these traditionally separate disciplines and collaboratively enhance the reliability and accuracy of our models by leveraging our broad, collective expertise.