The Romulus Simulations

High resolution cosmological simulations with improved supermassive black hole physics

gas temperature Romulus — Large-scale Structure in Romulus. A map of the gas temperature (hot = red, cold = blue) taken from a slab of the Romulus25 cosmological volume. Patches of hot gas exist around massive galaxies in part due to feedback from active galactic nuclei powered by supermassive black holes.

Overview

The Romulus simulations are large-scale cosmological simulations with resolution on par with the highest resolution simulations of this type run to date. The simulations are run with the most current cosmological parameters. Our flagship simulation is Romulus25, a uniform cosmological volume of 25 Mpc per side (about 80 million light years). Romulus25 provides a sample of 1000s of galaxies ranging from dwarf galaxies to massive galaxies at the centers of small groups. We are currently running a suite of zoom-in simulations (cosmological simulations focusing on the formation of only a single object, rather than a large volume) of massive galaxy groups and clusters (10¹³ to 10¹⁵ M_sol) to compliment the dataset provided by Romulus25. The first and most impressive of these is RomulusC, the highest resolution cosmological simulation ever done of a galaxy cluster. All together, the Romulus simulations will allow us to explore galaxy evolution in a variety of environments.

A novel implementation of SMBH physics

An important and unique strength of the Romulus simulations is the careful implementation of SMBH physics, designed to provide a physically motivated sub-grid model for SMBH formation, dynamics, growth, and feedback that will be suited to study questions relevant to modern and future observations of SMBHs and active galactic nuclei (AGN).

Seeding SMBHs in the early Universe based on gas properties allows Romulus to predict where and when SMBHs grow independent of any assumptions about what galaxies they exist in. It also allows us to follow SMBH growth at early times and in a variety of environments, including dwarf and satellite galaxies.

An accretion model that accounts for angular momentum support is crucial for modeling SMBH growth in disk-dominated galaxies. By connecting accretion to the gas kinematics, Romulus can give us a better picture of the different modes of SMBH growth (e.g. growth within disk galaxies vs actively merging galaxies).

Accounting for unresolved dynamical friction acting on SMBHs allows Romulus to accurately track the orbital evolution of SMBHs within galaxies to sub-kpc accuracy. This is crucial for understanding phases of SMBH growth during perturvative events like mergers. It is also important for modeling when and where SMBHs will form binaries and potentially merge to better interpret and predict results from future gravitational wave missions like LISA.

A careful implementation of feedback, combined with improved hydrodynamics and high resolution, allows for an accurate representation of how SMBHs interact not only with their immediate environment, but the host galaxy as a whole. Our model is able to avoid any ad hoc prescriptions for wind or "bubble" formation that often require heavy handed assumptions about the nature of SMBH feedback.

Dynamical Friction Model — Dynamical Friction At Work. A comparison that shows why the model for dynamical friction I've developed is an important improvement over previous approaches. These plots show the results of test simulations examining the orbital evolution of a SMBH conducted at the same resolution as the Romulus simulations. The theoretical prediction is that the SMBH should sink to the center in a few billion years (Gyr). The model with the dynamical friction correction (**blue**) does very well. The model with no correction (**cyan**) fails to sink after 6 billion years. The **red** line represents what we would find were we to use the same methods normally employed by large cosmological simulations lke Illustris (the SMBH unrealistically sinks immediately to the center)

Using Romulus Data

While the data from the simulations are not publicly available, we are very open to anyone working with it. We store a variety of halo properties within the TANGOS database framework (also have a look at the paper that Andrew Pontzen and I recently wrote). It is easy to access properties and profiles of all galaxies and their evolution through time in each simulation via either a python or web-based interface. If you would like to analyze this data, please contact me personally.

Research