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January 25, 2026EntropyOpen Access

Percolation with Distance-Dependent Site Occupational Probabilities

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An inverse percolation model reveals how tumor proximity alters site removal probabilities, indicating cancer therapy impacts.

This research aims to explore the effects of distance-dependent site occupational probabilities in a percolation model focused on tumor dynamics.
Introduced a novel inverse percolation model with distance-dependent site removal probabilities.
Analyzed the variation of the removal probability based on the distance from a central point (tumor).
Examined the structural properties of the percolation system as influenced by varying the parameter qp.
Establishment of a new critical percolation threshold of approximately pc=0.20, much lower than the standard pc=0.5927.
Demonstrated significant dependence of the spanning cluster size on qp.
Noted a strong correlation between the total number of clusters and the value of qp.

Lambrou et al. (2026) studied this question.

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