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Data · dataset · 2020

Collective Dissipative Structures, Force Flow Reciprocity, and the Foundations of Perception Action Mutuality. Benjamin De Bari, James A. Dixon, Dilip Kondepudi, & Bruce Kay

Listed in Teesside University Research Data Repository

This paper explored the coordination-like phenomena observed in collective dissipative structures.

Description

We observed the coordination of two self-organized electrical structures that oscillated together in a shared electrical field. The system is called the Electrical Self-Organized Foraging Implementation (E-SOFI).

The structures are coupled by this field and settle into stable oscillatory regimes defined by their relative phase. We also observed the oscillatory dynamics of simulated electrical structures, using a computational model called the Charge Depletion Model (CDM; De Bari et al., 2019). We predicted that both in-phase (zero radians relative phase) and anti-phase (pi radians relative phase) would be stable oscillatory modes for the physical and simulated system.

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Previous work has demonstrated that this system self-selects for states of maximal current. We predicted that the model would demonstrate differential stability of in-phase and anti-phase modes, in accordance with whichever mode produced the greater current. This data set includes the digitally tracked positions of the physical structures, gathered from video data.

One data set demonstrated in-phase coordination, and another demonstrated anti-phase coordination. Also included are corresponding data from simulations of the physical model. Simulations tested the existence of the in-phase and anti-phase modes, and the current conducted during the coordination.

Simulations were conducted across a parameter space that varied the stability of the in- and anti-phase coordination modes. We demonstrated stability in the in-phase coordination mode, and potential meta-stability of the anti-phase mode in the physical system. Simulations suggested that within a reasonable parameter space the anti-phase mode can be made stable.

Simulations also revealed that within a given parameter space, whichever mode produces greater current is also more stable. An R Markdown file includes the code to compute the relative phase of both the physical and simulated data, as well as the code used to produce the plots in the published manuscript.

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Catalogue records · 1

Topics

Inferred from text
Fluid mechanics and thermal engineering 70% · Video 75%
Provenance · 1 source records, 12 field assertions
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