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Explore the fascinating challenge of tracking odor sources in chaotic, windy environments through this 29-minute journal club discussion. Discover how organisms and algorithms can locate faint signals in turbulent flows where information comes only from rare, random encounters with passive tracers. Learn about high-fidelity numerical simulations that investigate quasi-optimal search strategies designed to minimize the average time needed to find sources. Examine the structure of these strategies and their comparison to the well-known infotaxis heuristic, understanding how optimal behavior in strong mean winds resembles biological "casting" patterns—zigzag searches followed by returns to origin that create characteristic square-root scaling of displacement over time. Gain insights into theoretical estimates for search duration in very low detection probability scenarios, supported by Monte Carlo simulation agreement. Understand applications for both natural biological behaviors and the design of robotic or algorithmic search systems operating in uncertain environments. The discussion features speaker Robin Heinonen from the University of Genova and is moderated by Emmanuel Villermaux from Physical Review Fluids and Aix-Marseille University, focusing on the research paper "Optimal trajectories for Bayesian olfactory search in turbulent flows: The low information limit and beyond."
