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arxiv: cond-mat/0505440 · v1 · pith:E2HK4GRYnew · submitted 2005-05-18 · ❄️ cond-mat.stat-mech · cond-mat.dis-nn

Target-searching on the percolation

classification ❄️ cond-mat.stat-mech cond-mat.dis-nn
keywords hunterpercolationtargetscalingdistancetarget-searchingaboveattempts
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We study target-searching processes on a percolation, on which a hunter tracks a target by smelling odors it emits. The odor intensity is supposed to be inversely proportional to the distance it propagates. The Monte Carlo simulation is performed on a 2-dimensional bond-percolation above the threshold. Having no idea of the location of the target, the hunter determines its moves only by random attempts in each direction. For lager percolation connectivity $p\gtrsim 0.90$, it reveals a scaling law for the searching time versus the distance to the position of the target. The scaling exponent is dependent on the sensitivity of the hunter. For smaller $p$, the scaling law is broken and the probability of finding out the target significantly reduces. The hunter seems trapped in the cluster of the percolation and can hardly reach the goal.

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