Olfactory search at high Reynolds number

Abstract

Locating the source of odor in a turbulent environment-a common behavior for living organisms-is nontrivial because of the random nature of mixing. Here we analyze the statistical physics aspects of the problem and propose an efficient strategy for olfactory search that can work in turbulent plumes. The algorithm combines the maximum likelihood inference of the source position with an active search. Our approach provides the theoretical basis for the design of olfactory robots and the quantitative tools for the analysis of the observed olfactory search behavior of living creatures (e.g., odor-modulated optomotor anemotaxis of moths).

Figure 1

A snapshot of the model odor field (y = 100). Broken line bounds the parabolic region where most odor patches are concentrated. Graph on the bottom represents the probability density function of patch distribution at y = 100. Arrow indicates the mean wind direction.

Figure 2

(a) An odor patch arriving from P = (x₀, y₀) detected at R. Circles indicate possible source locations inside the “causality” cone with the vertex at P. Broken line is the boundary of the parabolic region corresponding to relatively high likelihood of source location. The nodes inside the parabolic region are shown as filled circles. (b) A counterturning trajectory inside the cone.

Figure 3

Typical search trajectories for the two algorithms. The initial position is (, 100). (a) The search is performed inside causality cones. (b) The modified search, where only the points inside the parabolic high-likelihood regions are searched. Arrow indicates the mean wind direction. The broken lines show the region of high probability to encounter an odor patch.

Figure 4

Histogram of the search time obtained numerically by using Monte Carlo simulations. (a) With initial condition (0, 50). (b) With initial condition (, 50). Solid line shows the histogram for the passive search algorithm, broken line, for the active search algorithm. Note the logarithmic scale of t.