Coarse graining flow of spin foam intertwiners

Simplicity constraints play a crucial role in the construction of spin foam models, yet their effective behavior on larger scales is scarcely explored. In this article we introduce intertwiner and spin net models for the quantum group SU(2)(k) x SU(2)(k), which implement the simplicity constraints analogous to four-dimensional Euclidean spin foam models, namely the Barrett-Crane (BC) and the Engle-Pereira-Rovelli-Livine/Freidel-Krasnov (EPRL/FK) model. These models are numerically coarse grained via tensor network renormalization, allowing us to trace the flow of simplicity constraints to larger scales. In order to perform these simulations we have substantially adapted tensor network algorithms, which we discuss in detail as they can be of use in other contexts. The BC and the EPRL/FK model behave very differently under coarse graining: While the unique BC intertwiner model is a fixed point and therefore constitutes a two-dimensional topological phase, BC spin net models flow away from the initial simplicity constraints and converge to several different topological phases. Most of these phases correspond to decoupling spin foam vertices; however we find also a new phase in which this is not the case, and in which a nontrivial version of the simplicity constraints holds. The coarse graining flow of the BC spin net models indicates furthermore that the transitions between these phases are not of second order. The EPRL/FK model by contrast reveals a far more intricate and complex dynamics. We observe an immediate flow away from the original simplicity constraints; however, with the truncation employed here, the models generically do not converge to a fixed point. The results show that the imposition of simplicity constraints can indeed lead to interesting and also very complex dynamics. Thus we need to further develop coarse graining tools to efficiently study the large scale behavior of spin foam models, in particular for the EPRL/FK model.