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In astrophysics, experiments are impossible. We thus must rely exclusively onobservational data. Other observational sciences increasingly leverage causalinference methods, but this is not yet the case in astrophysics. Here weattempt causal discovery for the first time to address an important openproblem in astrophysics: the (co)evolution of supermassive black holes (SMBHs)and their host galaxies. We apply the Peter-Clark (PC) algorithm to acomprehensive catalog of galaxy properties to obtain a completed partiallydirected acyclic graph (CPDAG), representing a Markov equivalence class overdirected acyclic graphs (DAGs). Central density and velocity dispersion arefound to cause SMBH mass. We test the robustness of our analysis by randomsub-sampling, recovering similar results. We also apply the Fast CausalInference (FCI) algorithm to our dataset to relax the hypothesis of causalsufficiency, admitting unobserved confounds. Hierarchical SMBH assembly mayprovide a physical explanation for our findings.

Causa prima: cosmology meets causal discovery for the first time