Collective behavior and memory states in flow networks with tunable bistability.

Area of Science:

• Complex Systems
• Nonlinear Dynamics
• Electronic Circuit Design

Background:

• Multistability and hysteresis are well-researched in mechanical systems but challenging to replicate in experimental flow networks.
• Natural biological flow networks, such as vasculature, display complex nonlinear behaviors crucial for fluid transport.
• Understanding multistable flows could offer insights into the functionality of these natural systems.

Purpose of the Study:

• To experimentally probe multistable flow phenomena using an analogous model system.
• To investigate the generation of complex global memory states in an electronic network.
• To explore avalanching behavior and the encoding of arbitrary interactions within the system.

Main Methods:

• Utilized an electronic network composed of hysteretic bistable resistors.
• Engineered resistors with tunable negative differential resistivity.
• Analyzed voltage patterns to characterize global memory states and interactions.

Main Results:

• Successfully generated complex global memory states in the form of voltage patterns.
• Demonstrated that tunable nonlinearity of circuit elements mediates memory state generation.
• Observed avalanching behavior driven by effective interactions and showed how to encode explicit interactions.

Conclusions:

• The developed electronic network serves as a viable model system for studying multistability and hysteresis in flow phenomena.
• Tunable nonlinear electronic components can effectively replicate complex memory states and interactions found in natural systems.
• This approach offers a platform for further research into complex dynamics and memory in analogous systems.