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More Is Faster: Why Population Size Matters in Biological Search.

Jannatul Ferdous¹, George Matthew Fricke^1,2, Melanie E Moses^1,3,4

¹Department of Computer Science, The University of New Mexico, Albuquerque, New Mexico, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|May 16, 2024

Summary

This summary is machine-generated.

This study introduces a new mathematical model for predicting when the first of many searchers will find a target. The model shows that initial contact times decrease with more searchers and larger search areas.

Keywords:

collective search extreme first passage time foraging immunity initial first contact time

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Area of Science:

Mathematical Biology
Collective Behavior
Search Theory

Background:

Biological systems often involve multiple agents searching for targets.
The timing of the first encounter is crucial in many scenarios.
Existing models lack predictions for first contact times with multiple searchers.

Purpose of the Study:

To develop a novel mathematical model for predicting initial first contact times.
To analyze the impact of searcher number, distribution, and initial distances.
To compare the new model with the extreme first passage time approach.

Main Methods:

Developed a mathematical model for random searcher-target distributions in a volume.
Compared model predictions with the extreme first passage time approach.
Investigated effects of varying searcher/target density and initial distances.

Main Results:

Initial first contact time decreases linearly with search volume and number of searchers at constant density.
For a single target and co-located searchers, the relationship shifts from linear to logarithmic decrease with increasing searchers.
Initial first contact times are significantly faster than average search times and decrease with more searchers.

Conclusions:

The developed model accurately predicts initial first contact times in collective search scenarios.
Initial contact times are highly sensitive to the number of searchers, unlike average search times.
This underappreciated phenomenon has implications for biology and other collective search problems.