Abstract
We present an algorithm which explores permutation symmetries to describe the time evolution of agent-based epidemic models. The main idea to improve computation times relies on restricting the stochastic process to one sector of the vector space, labeled by a single permutation eigenvalue. In this scheme, the transition matrix reduces to block diagonal form, enhancing computational performance.
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