From the 1 of 9 linked papers with an AI index.
9 papers
Learning Backward Transport for Source Localization
Maurizio Carbone, Lorenzo Piro
The paper introduces a backward‑transport approach, using Schrödinger bridge theory and Langevin dynamics, to infer the location of a chemical source from concentration measurement…
Smart strategies to navigate turbulent odor plumes reorienting to local wind
Lorenzo Piro, Maurizio Carbone, Luca Biferale +4
Olfactory search in turbulent environments is a sensorimotor problem that many animals solve with remarkable efficiency, yet replicating this ability in artificial systems is an en…
Olfactory pursuit: catching a moving odor source in complex flows
Maurizio Carbone, Lorenzo Piro, Robin A. Heinonen +3
Locating and intercepting a moving target from possibly delayed, intermittent sensory signals is a paradigmatic problem in decision-making under uncertainty, and a fundamental chal…
Nonequilibrium energetics of sensing and actuation by a smart active particle
Luca Cocconi, Benoît Mahault, Lorenzo Piro
Smart active agents must allocate finite energetic resources across distinct functions, yet the underlying thermodynamic trade-offs remain poorly understood. Here, we introduce a m…
Adaptive shape control for microswimmer navigation in turbulence
Jingran Qiu, Lorenzo Piro, Luca Biferale +3
Navigation in turbulent environments is a fundamental challenge for biological and artificial microswimmers. While most existing studies focus on adapting motility or steering, the…
TURB-Smoke. A database of Lagrangian pollutants emitted from point-sources and dispersed in turbulent flows
Luca Biferale, Fabio Bonaccorso, Niccolò Cocciaglia +2
Identifying the location and characteristics of pollution sources in turbulent flows is challenging, especially for environmental monitoring and emergency response, due to sparse,…