  We consider the problem of recovering a subhypergraph based on an observed
adjacency tensor corresponding to a uniform hypergraph. The uniform hypergraph
is assumed to contain a subset of vertices called as subhypergraph. The edges
restricted to the subhypergraph are assumed to follow a different probability
distribution than other edges. We consider both weak recovery and exact
recovery of the subhypergraph, and establish information-theoretic limits in
each case. Specifically, we establish sharp conditions for the possibility of
weakly or exactly recovering the subhypergraph from an information-theoretic
point of view. These conditions are fundamentally different from their
counterparts derived in hypothesis testing literature.
