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Register a new userAre Particles Self-Organized Systems?
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Authors
Vladimir A. Manasson
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Elementary particles possess quantized values of charge and internal angular momentum or spin. These characteristics do not change when the particles interact with other particles or fields as long as they preserve their entities. Quantum theory does not explain this quantization. It is introduced into the theory a priori. An interacting particle is an open system and thus does not obey conservation laws. However, an open system may create dynamically stable states with unchanged dynamical variables via self-organization. In self-organized systems stability is achieved through the interplay of nonlinearity and dissipation. Can self-organization be responsible for particle formation? In this paper we develop and analyze a particle model based on qualitative dynamics and the Feigenbaum universality. This model demonstrates that elementary particles can be described as self-organized dynamical systems belonging to a wide class of systems characterized by a hierarchy of period-doubling bifurcations. This semi-qualitative heuristic model gives possible explanations for charge and action quantization, and the origination and interrelation between the strong, weak, and electromagnetic forces, as well as SU(2) symmetry. It also provides a basis for particle taxonomy endorsed by the Standard Model. The key result is the discovery that the Planck constant is intimately related to elementary charge.
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We propose a dynamical model in which a network structure evolves in a self-organized critical (SOC) manner and explain a possible origin of the emergence of fractal and small-world networks. Our model combines a network growth and its decay by failures of nodes. The decay mechanism reflects the instability of large functional networks against cascading overload failures. It is demonstrated that the dynamical system surely exhibits SOC characteristics, such as power-law forms of the avalanche size distribution, the cluster size distribution, and the distribution of the time interval between intermittent avalanches. During the network evolution, fractal networks are spontaneously generated when networks experience critical cascades of failures that lead to a percolation transition. In contrast, networks far from criticality have small-world structures. We also observe the crossover behavior from fractal to small-world structure in the network evolution.
In this paper, a simple dynamical model in which fractal networks are formed by self-organized critical (SOC) dynamics is proposed; the proposed model consists of growth and collapse processes. It has been shown that SOC dynamics are realized by the combined processes in the model. Thus, the distributions of the cluster size and collapse size follow a power-law function in the stationary state. Moreover, through SOC dynamics, the networks become fractal in nature. The criticality of SOC dynamics is the same as the universality class of mean-field theory. The model explains the possibility that the fractal nature in complex networks emerges by SOC dynamics in a manner similar to the case with fractal objects embedded in a Euclidean space.
Multimode fibres (MMFs) are attracting interest for complex spatiotemporal dynamics, and for ultrafast fibre sources, imaging and telecommunications. This new interest is based on three key properties: their high spatiotemporal complexity (information capacity), the important role of disorder, and complex intermodal interactions. To date, phenomena in MMFs have been studied only in limiting cases where one or more of these properties can be neglected. Here we study MMFs in a regime in which all these elements are integral. We observe a spatial beam-cleaning process preceding spatiotemporal modulation instability. We show that the origin of these processes is a universal unstable attractor in graded-index MMFs. Both the self-organization of the attractor, as well as its instability, are caused by intermodal interactions characterized by cooperating disorder, nonlinearity and dissipation. The demonstration of a disorder-enhanced nonlinear process in MMF has important implications for telecommunications, and the multifaceted complexity of the dynamics showcases MM waveguides as ideal laboratories for many topics and applications in complexity science.
Introduced by the late Per Bak and his colleagues, self-organized criticality (SOC) has been one of the most stimulating concepts to come out of statistical mechanics and condensed matter theory in the last few decades, and has played a significant role in the development of complexity science. SOC, and more generally fractals and power laws, have attacted much comment, ranging from the very positive to the polemical. The other papers in this special issue (Aschwanden et al, 2014; McAteer et al, 2014; Sharma et al, 2015) showcase the considerable body of observations in solar, magnetospheric and fusion plasma inspired by the SOC idea, and expose the fertile role the new paradigm has played in approaches to modeling and understanding multiscale plasma instabilities. This very broad impact, and the necessary process of adapting a scientific hypothesis to the conditions of a given physical system, has meant that SOC as studied in these fields has sometimes differed significantly from the definition originally given by its creators. In Baks own field of theoretical physics there are significant observational and theoretical open questions, even 25 years on (Pruessner, 2012). One aim of the present review is to address the dichotomy between the great reception SOC has received in some areas, and its shortcomings, as they became manifest in the controversies it triggered. Our article tries to clear up what we think are misunderstandings of SOC in fields more remote from its origins in statistical mechanics, condensed matter and dynamical systems by revisiting Bak, Tang and Wiesenfelds original papers.
Stationarity of the constituents of the body and of its functionalities is a basic requirement for life, being equivalent to survival in first place. Assuming that the resting state activity of the brain serves essential functionalities, stationarity entails that the dynamics of the brain needs to be regulated on a time-averaged basis. The combination of recurrent and driving external inputs must therefore lead to a non-trivial stationary neural activity, a condition which is fulfilled for afferent signals of varying strengths only close to criticality. In this view, the benefits of working vicinity of a second-order phase transition, such as signal enhancements, are not the underlying evolutionary drivers, but side effects of the requirement to keep the brain functional in first place. It is hence more appropriate to use the term self-regulated in this context, instead of self-organized.
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