  Clustering $\unicode{x2013}$ the tendency for neighbors of nodes to be
connected $\unicode{x2013}$ quantifies the coupling of a complex network to its
latent metric space. In random geometric graphs, clustering undergoes a
continuous phase transition, separating a phase with finite clustering from a
regime where clustering vanishes in the thermodynamic limit. We prove this
geometric-to-nongeometric phase transition to be topological in nature, with
anomalous features such as diverging entropy as well as atypical finite size
scaling behavior of clustering. Moreover, a slow decay of clustering in the
nongeometric phase implies that some real networks with relatively high levels
of clustering may be better described in this regime.
