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Computing The Analytic Connectivity of A Uniform Hypergraph

The analytic connectivity, proposed as a substitute of the algebraic connectivity in the setting of hypergraphs, is an important quantity in spectral hypergraph theory. The definition of the analytic connectivity for a uniform hypergraph involves a series of optimization problems (POPs) associated with the Laplacian tensor of the hypergraph with nonnegativity constraints and a sphere constraint, which poses difficulties in computation. To reduce the involved computation, properties on the algebraic connectivity are further exploited, and several important structured uniform hypergraphs are shown to attain their analytic connectivities at vertices of the minimum degrees, hence admit a relatively less computation by solving a small number of POPs. To efficiently solve each involved POP, we propose a feasible trust region algorithm ({\tt FTR}) by exploiting their special structures. The global convergence of {\tt FTR} to the second-order necessary conditions points is established, and numerical results for both small and large size examples with comparison to other existing algorithms for POPs are reported to demonstrate the efficiency of our proposed algorithm.