Synopsis and Introduction

Haken, Hermann

doi:10.1007/978-3-642-69421-9_2

Cited by 279 publications

(360 citation statements)

References 4 publications

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“…In the following the terms and models of synergetics are used that were introduced to cognition research by Haken (1983) and Haken and Stadler (1990). Haken's synergetics is a self-organization theory based on general systems theory and thermodynamics (Haken 1977).…”

Section: Synergetics In Cognition Researchmentioning

confidence: 99%

“…These dynamics of cognitive processes may be described in terms of self-organization theories such as Haken's synergetics (Haken 1977). In this theoretical context spontaneous alternations of perceived motion directions have been considered as discontinuous phase transitions between the corresponding neuronal attractors (Ditzinger and Correspondence to: M. Stadler Haken 1989).…”

Section: Introductionmentioning

confidence: 99%

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Continuous phase transitions in the perception of multistable visual patterns

Kruse

Carmesin

Pahlke

et al. 1996

Biological Cybernetics

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The phenomenon of stroboscopic alternative motion exhibits five different percepts that are seen with an increase in the frequency of presentation: (a) succession, (b) fluttering motion, (c) reversible clockwise and counter-clockwise turning motion, (d) oppositional motion and (e) simultaneity. From a synergetic point of view the increase in frequency is a control parameter and the different percepts are order parameters with phase transitions in between. The neural network model of Carmesin and Arndt is applied to receive predictions about hysteresis and phase transitions between these order parameters. Empirical data show the different motion percepts (b), (c) and (e) have lognormal distributions. Following the theoretical model, it is argued that there are three different phases, (a), (c) and (e), with two continuous phase transitions, (b) and (d), between them. The experimental data substantially match the theoretical assumptions.

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Section: Synergetics In Cognition Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Continuous phase transitions in the perception of multistable visual patterns

Kruse

Carmesin

Pahlke

et al. 1996

Biological Cybernetics

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“…We show that amplitude-phase coupling, a concept common in different fields, is necessary for the formation of the chimera states. Synchronization is a common phenomenon in interacting nonlinear dynamical systems in various fields of research such as physics, chemistry, biology, engineering, or socioeconomic sciences [1][2][3]. While a lot of knowledge has been gained on the origin of complete synchronization, more complex partial synchronization patterns have only recently become the focus of intense research.…”

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confidence: 99%

Amplitude-phase coupling drives chimera states in globally coupled laser networks

et al. 2015

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For a globally coupled network of semiconductor lasers with delayed optical feedback, we demonstrate the existence of chimera states. The domains of coherence and incoherence that are typical for chimera states are found to exist for the amplitude, phase, and inversion of the coupled lasers. These chimera states defy several of the previously established existence criteria. While chimera states in phase oscillators generally demand nonlocal coupling, large system sizes, and specially prepared initial conditions, we find chimera states that are stable for global coupling in a network of only four coupled lasers for random initial conditions. The existence is linked to a regime of multistability between the synchronous steady state and asynchronous periodic solutions. We show that amplitude-phase coupling, a concept common in different fields, is necessary for the formation of the chimera states. Synchronization is a common phenomenon in interacting nonlinear dynamical systems in various fields of research such as physics, chemistry, biology, engineering, or socioeconomic sciences [1][2][3]. While a lot of knowledge has been gained on the origin of complete synchronization, more complex partial synchronization patterns have only recently become the focus of intense research. We still lack a full understanding of these phenomena, and a very prominent example are chimera states where an ensemble of identical elements self-organizes into spatially separated coexisting domains of coherent (synchronized) and incoherent (desynchronized) dynamics [4,5]. Since their first discovery a decade ago many theoretical investigations of coupled phase oscillators and other simplified models have been carried out [6,7] [7,16,17], e.g., spiral wave chimeras [18,19], FitzHugh-Nagumo neural systems [20], Stuart-Landau oscillators [21][22][23], where pure amplitude chimeras [24] were found, or quantum interference devices [25]. In real-world systems chimera states might play a role, e.g., in the unihemispheric sleep of birds and dolphins [26], in neuronal bump states [27,28], in power grids [29], or in social systems [30].Although no universal mechanism for the formation of chimera states has yet been established, three general essential requirements have been found in many studies: (i) a large number of coupled elements, (ii) non-local coupling, and (iii) specific initial conditions. These were primarily derived from the phase oscillator model [7] but also apply to other systems. If these conditions are not met, the chimera states tend to have very short lifetimes. Recent studies, however, suggest that these paradigms can be broken and chimera states are observed also for small system sizes [31], global coupling [15,23,32,33] and random initial conditions [34].Surprisingly, chimera states appear at the interface of independent fields of research putting together different scientific communities. Recent examples are quantum chimera state [35] or coexistence of coherent and incoherent patterns with respect to the modes of an optical com...

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“…Static stability and deforming the potential field will be discussed in more detail in Chapter 3. For example, the potential force field [29,32] for a nonlinear spring system can be written in kinematic form (no dynamics) aṡ…”

Section: C11 Backgroundmentioning

confidence: 99%

Collective systems:physical and information exergies.

Robinett¹,

Wilson²

2007

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Collective systems are typically defined as a group of agents (physical and/or cyber) that work together to produce a collective behavior with a value greater than the sum of the individual parts. This amplification or synergy can be harnessed by solving an inverse problem via an information-flow/communications grid: given a desired macroscopic/collective behavior find the required microscopic/individual behavior of each agent and the required communications grid. The goal of this report is to describe the fundamental nature of the Hamiltonian function in the design of collective systems (solve the inverse problem) and the connections between and values of physical and information exergies intrinsic to collective systems. In particular, physical and information exergies are shown to be equivalent based on thermodynamics and Hamiltonian mechanics.3 Acknowledgment

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Synopsis and Introduction

Cited by 279 publications

References 4 publications

Continuous phase transitions in the perception of multistable visual patterns

Continuous phase transitions in the perception of multistable visual patterns

Amplitude-phase coupling drives chimera states in globally coupled laser networks

Collective systems:physical and information exergies.

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