Genetically modified halos: towards controlled experiments in $\Lambda$CDM galaxy formation

Understand

We propose a method to generate `genetically-modified' (GM) initial conditions for high-resolution simulations of galaxy formation in a cosmological context.

• Building on the Hoffman-Ribak algorithm, we start from a reference simulation with fully random initial conditions, then make controlled changes to specific properties of a single halo (such as its mass and merger history).
• The algorithm demonstrably makes minimal changes to other properties of the halo and its environment, allowing us to isolate the impact of a given modification.
• As a significant improvement over previous work, we are able to calculate the abundance of the resulting objects relative to the reference simulation.