  In astrophysics, experiments are impossible. We thus must rely exclusively on
observational data. Other observational sciences increasingly leverage causal
inference methods, but this is not yet the case in astrophysics. Here we
attempt causal discovery for the first time to address an important open
problem in astrophysics: the (co)evolution of supermassive black holes (SMBHs)
and their host galaxies. We apply the Peter-Clark (PC) algorithm to a
comprehensive catalog of galaxy properties to obtain a completed partially
directed acyclic graph (CPDAG), representing a Markov equivalence class over
directed acyclic graphs (DAGs). Central density and velocity dispersion are
found to cause SMBH mass. We test the robustness of our analysis by random
sub-sampling, recovering similar results. We also apply the Fast Causal
Inference (FCI) algorithm to our dataset to relax the hypothesis of causal
sufficiency, admitting unobserved confounds. Hierarchical SMBH assembly may
provide a physical explanation for our findings.
