Regensburg 2019 – wissenschaftliches Programm

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BP: Fachverband Biologische Physik

BP 6: Poster I

BP 6.28: Poster

Montag, 1. April 2019, 17:30–19:30, Poster B2

Memory capacity of a flow network — •Komal Bhattacharyya and Karen Alim — Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany

The slime mould Physarum polycephalum is a very simple unicellular but seemingly intelligent organism with a network-like body. Its complex behaviour requires the ability to propagate, store and process information. Recently, it has been shown that Physarum propagates information about stimuli with the fluid flows throughout its network. And most inspiringly, Physarum was observed to adapt its networks tube radii network-wide in response to stimuli, reaching a steady-state as a long term response to the applied stimuli, keeping a memory of the stimuli in its network morphology. Inspired by this observation we here investigate the capacity to store information about previous stimuli in the morphology of an adaptive flow network. We model the organism as a flow network whose radii can change when optimising the network to have least energy dissipation. We observe how the system reacts to localised changes and the timescale of its responses to applied stimuli by numerical simulation. Through theoretical understanding we aim to pin-point to the information storing and processing capabilities of adaptive flow networks in general and Physarum networks specifically.