Steady-State Distributions of Random Walks with (some) Memory
In order to find food the bacterium E. coli performs a random-walk whose moves are influenced by its memory of the past. The details of the motion are thought to be well understood. However, to understand its behavior one must be able to deduce the steady-state probability distribution of the bacterium in a given environment. In this talk a method for solving a simplified model of the motion, which involves a much more realistic description of the influence of the memory on the motion, will be introduced in some detail. The resulting steady-state distribution for different scenarios will then be analyzed and contrasted with previous treatments.
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