Decoupling local and synchronization transitions yields a linearly convergent MTTA algorithm that is accelerated to quadratic convergence and represented in tensor-train format, enabling computation on systems with up to billions of states.
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Tensor methods for the computation of MTTA in large systems of loosely interconnected components
Decoupling local and synchronization transitions yields a linearly convergent MTTA algorithm that is accelerated to quadratic convergence and represented in tensor-train format, enabling computation on systems with up to billions of states.