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Searching for clusters of targets under stochastic resetting

2021/11/01 by Georgia R. Calvert, M. R. Evans, Martin R. Evans
Biochemistry, Genetics and Molecular Biology · Engineering · Immunology and Microbiology · Mathematics · Physics and Astronomy · #Algorithm #Combinatorics #Computer science #Diffusion #Diffusion and Search Dynamics #Dimension (graph theory) #Engineering #HIV Research and Treatment #Immunotherapy and Immune Responses #Limiting #Mathematics #Physics #Relevance (law) #cond-mat.stat-mech

paper · pdf · doi:10.1140/epjb/s10051-021-00238-0

published in The European Physical Journal B 94(11) (Springer Science+Business Media) · 9 pages, 3 figures, accepted for European Physical Journal B

openalex publication_date 2021/11/01 · arxiv created 2021/11/03 · arxiv updated 2021/12/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Abstract We consider diffusion under stochastic resetting to the origin in one dimension and compute the mean time to find both of two targets placed either side of the origin. A surprising result is that increasing the distance between two targets can decrease the overall search time. We compute the optimal arrangement of two targets in limiting cases. We generalise to obtain recursive expressions for the mean time to find all of multiple targets. We discuss the relevance to real-world problems of locating multiple targets such as proteins locating clusters of DNA lesions. Graphic abstract

Citations