Kengne, JacquesKoinfo, Jean BaptisteRajagopal, KarthikeyanRamadoss, Janarthanan...
21页查看更多>>摘要：The study of complex nonlinear phenomena certainly represents a very hot ongoing research topic owing to recently published works. While a large number of contributions deal with systems with symmetry, very few works are concerned with those without any symmetry property. In this contribution, we introduce a novel asymmetric jerk system whose nonlinearity is in the form of a six-order Tchebytchev polynomial of the fundamental variable. The new system distinguishes by the presence of six equilibrium points symmetrically distributed along the x-axis. Three of these points are always unstable (regardless the values of parameter) while each of the three others undergoes Hopf type bifurcation at three different critical values of the control parameter resulting to self-excited coexisting behaviors such as: (i) a limit cycle and a pair of stable fixed points; (ii) a pair of limit cycles and a stable fixed point; (iii) a stable fixed point, a limit cycle and a chaotic attractor; just to cite a few. These features are studied by combining both analytical and numerical methods. More importantly, various parameter ranges are depicted where the new jerk system with Tchebytchev polynomials demonstrates extremely complex and striking nonlinear patterns such as antimonotonicity, hysteresis and coexisting bifurcation branches. These two latter properties give rise to multiple (i.e. two, three or four) coexisting (periodic and chaotic) attractors. Cross sections of the basins of attraction are provided to illustrate the magnetization of the state space caused by the various competing dynamics. The control of multistability in the new system is achieved via linear augmentation scheme. The practical feasibility of the new system is supported by a series of PSPICE simulations utilizing an electronic analogue of the proposed jerk system. The combination of features found in the new jerk system with Tchebytchev polynomials are rarely reported and thus merits dissemination. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:
NSTL
Elsevier
Ke, JianhongLi, Ping-PingLin, Zhenquan
14页查看更多>>摘要：We study the evolutionary snowdrift game with an update rule of dissatisfaction-driven replicator on regular lattices, in which there exists a threshold value K of dissatisfaction dividing the update rule into unconditional imitation and probability replication. It is found that under the random initial state with f(c0) = 0.5, the equilibrium cooperation frequency fc against the cost-to-benefit ratio r has a step-like piecewise structure when K is small and then neighboring plateaus gradually connect together as K increases, and finally f(c) will take the typical continuous form observed in the game system with the conventional replicator. By analyzing the stability and microscopic evolution of local strategy configurations, we interpret qualitatively both the emergence and disappearance of discontinuous transitions at several critical values of r. And we also enumerate some snapshots of spatial patterns of strategy distribution to exhibit how the competitive system evolves from one dynamical behavior to another. Numerical simulations show that the system can evolve to a mixed state with cooperators and defectors coexisting in the case of r < 2/3, while it can certainly end up in a pure phase only with D agents in the case of r > 3/4. We further investigate the dynamics of our model by the master equation approach and then calculate the numerical computation results of f(c), in perfect accord with those obtained by numerical simulations. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Leng, HuiZhao, YiWang, Dong
12页查看更多>>摘要：In social contagions, an individual to trust the behavioral information transmitted by neighbors depends on the level of the social status of neighbors as well as the closeness degree with neighbors. From the view of network topology, we propose the trust probability with multiple influence factors: node degree and the number of common neighbors. Furthermore, a weight factor is set to adjust the influence extent of the above two factors. As a result, in the context of the trust probability, we investigate social contagions with focus on social reinforcement and memory effect on networks, which are modeled by the threshold model. The message passing approach is adopted so as to formulate the state evolution of each node on the basis of network topology. Through extensive numerical simulations, we find that the trust probability can suppress social contagions, so does increasing the trust probability gap. Notably, the number of common neighbors as an influence factor of the trust probability is able to increase the final behavior adoption size, while node degree takes the opposite effect. The theoretical results are confirmed to agree well with the numerical results by the Monte Carlo method. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Boettcher, StefanGago, Paula A.Sibani, Paolo
8页查看更多>>摘要：Cooperative events requiring a rare large fluctuation are a defining characteristic for the onset of glassy relaxation across many materials. The importance of such intermittent events has been noted in systems as diverse as superconductors, metallic glasses, gels, colloids, and granular piles. Here, we show that prohibiting the attainment of new record-high energy fluctuations - by explicitly imposing a "lid"on the fluctuation spectrum - impedes further relaxation in the glassy phase. This lid allows us to directly measure the impact of record events on the evolving system in extensive simulations of aging in such vastly distinct glass formers as spin glasses and tapped granular piles. Interpreting our results in terms of a dynamics of records succeeds in explaining the ubiquity of both, the logarithmic decay of the energy and the memory effects encoded in the scaling of two-time correlation functions of aging systems. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Papastamatiou, KonstantinosKarakasidis, Theodoros
20页查看更多>>摘要：Upfront bubble detection is one of the holy grails in Financial Markets. In the present paper, in order to archive this goal, we consider two different methods based on the Log Periodic Power Law. We implement this early detection algorithms in the Greek Stock Market, which is a relatively "shallow"and underdeveloped market. We have examined a period from 1997 until the end of 2019, an epoch before the rise of COVID-19 virus. Using this methodology, we managed to detect with a relatively good accuracy the formation and the critical time for both positive and negative financial bubbles that occurred during the examination period. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
