ArticlePhysical review fluids2025
Optimal trajectories for Bayesian olfactory search in turbulent flows: The low information limit and beyond.
Article in Physical review fluids, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Fly navigational responses exploit plume-specific odor motion and gradient cues.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- TURB-Smoke. A database of Lagrangian pollutants emitted from point sources in turbulent flows with a mean wind.Scientific data · 2026Article
- Noise enhances odor source localization.ArXiv · 2026Article
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4 authors.
Funding
Abstract
In turbulent flows, tracking the source of a passive scalar cue requires exploiting the limited information that can be gleaned from rare, randomized encounters with the cue. When crafting a search policy, the most challenging and important decision is what to do in the absence of an encounter. In this work, we perform high-fidelity direct numerical simulations of a turbulent flow with a stationary source of tracer particles, and obtain quasi-optimal policies (in the sense of minimal average search time) with respect to the empirical encounter statistics [1-3]. We study the trajectories under such policies and compare the results to those of the infotaxis heuristic. In the presence of a strong mean wind, the optimal motion in the absence of an encounter is zigzagging (akin to the well-known insect behavior "casting") followed by a return to the starting location. The zigzag motion generates characteristic
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