Computing tensor Z-eigenvectors with dynamical systems
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We present a new framework for computing Z-eigenvectors of general tensors based on numerically integrating a dynamical system that must converge to a Z-eigenvector. Our motivation comes from our recent research on spacey random walks, where the long-term dynamics of a stochastic process are governed by a dynamical system that must converge to a Z-eigenvectors of a given transition probability tensor. Here, we apply the ideas more broadly to general tensors and find that our method can compute Z-eigenvectors that algebraic methods like the higher-order power method cannot compute.
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