On Diagonalizable Systems with Random Structure

Abstract. Diagonalizability plays an important role in the analysis and design of multiple-variable systems. A structured matrix is called structurally diagonalizable if almost all of its numerical realizations—obtained by assigning real values to its free entries—are diagonalizable. Structural diagonalizability is useful in the verification and optimization of various structural system properties. In this paper, we study the asymptotic probability distribution of structural diagonalizability for structured systems whose system matrices are represented by directed Erdős–Rényi random graphs. Leveraging a recently established graph-theoretic characterization of structural diagonalizability, we systematically analyze the distribution of structurally diagonalizable graphs under different edge-density regimes: for dense graphs, we prove that the system is almost always structurally diagonalizable; for graphs of medium density, we derive tight upper and lower bounds on the asymptotic probability of structural diagonalizability; and for extremely sparse graphs, we show that the asymptotic probability approaches 0. The theoretical results are validated through extensive numerical simulations under varying numbers of vertices and connection probabilities.