The European Physical Journal B最新文献

In this paper we investigate the dynamics of an extended form of a symmetric Duffing oscillator driven by a periodic force (F(t)=A cos omega t). The system is modeled by a second-order nonautonomous nonlinear ordinary differential equation, and controlled by seven parameters. Our study takes into account the ((omega ,A)) parameter plane of the system, consequently keeping the other five parameters fixed. We verify the existence of parameter regions for which the corresponding trajectories in the phase-space are periodic or chaotic, delimiting therefore such regions in the ((omega ,A)) parameter plane. Finally, we use this same ((omega ,A)) parameter plane to locate multistability regions. Examples of basins of attraction of coexisting periodic and chaotic attractors are presented, as well as the related attractors.

Projections of basins of attraction onto the xy plane of initial conditions for an extended forced Duffing oscillator. Black (Red) regions are related to a periodic (chaotic) attractor basin of attraction.

The last 25 years have seen the development of a significant literature within the subfield of econophysics which attempts to model economic inequality as the emergent property of systems of stochastically interacting agents. In this article, the literature surrounding this approach to the study of wealth and income distributions, henceforth the “random asset exchange” literature following the terminology of Sinha (Phys Scr 2003(T106):59, 2003), is thoroughly reviewed for the first time. The foundational papers of Drăgulescu and Yakovenko (Eur Phys J B 17(4):723–729, 2000), Chakraborti and Chakrabarti (Eur Phys J B 17(1):167–170, 2000), and Bouchaud and Mézard (Physica A 282(3):536–545, 2000) are discussed in detail, and principal canonical models within the random asset exchange literature are established. The most common variations upon these canonical models are enumerated and the successes and limitations of such models are discussed. The paper concludes with an argument that the literature should move in the direction of more explicit representations of economic structure and processes to acquire greater explanatory power.

In functionally complex systems, higher order connectivity is often revealed in the underlying geometry of networked units. Furthermore, such systems often show signatures of self-organised criticality, a specific type of non-equilibrium collective behaviour associated with an attractor of internal dynamics with long-range correlations and scale invariance, which ensures the robust functioning of complex systems, such as the brain. Here, we highlight the intertwining of features of higher order geometry and self-organised critical dynamics as a plausible mechanism for the emergence of new properties on a larger scale, representing the central paradigm of the physical notion of complexity. Considering the time-scale of the structural evolution with the known separation of the time-scale in self-organised criticality, i.e., internal dynamics and external driving, we distinguish three classes of geometries that can shape the self-organised dynamics on them differently. We provide an overview of current trends in the study of collective dynamics phenomena, such as the synchronisation of phase oscillators and discrete spin dynamics with higher order couplings embedded in the faces of simplicial complexes. For a representative example of self-organised critical behaviour induced by higher order structures, we present a more detailed analysis of the dynamics of field-driven spin reversal on the hysteresis loops in simplicial complexes composed of triangles. These numerical results suggest that two fundamental interactions representing the edge-embedded and triangle-embedded couplings must be taken into account in theoretical models to describe the influence of higher order geometry on critical dynamics.

In biological, glassy, and active systems, various tracers exhibit Laplace-like, i.e., exponential, spreading of the diffusing packet of particles. The limitations of the central limit theorem in fully capturing the behaviors of such diffusive processes, especially in the tails, have been studied using the continuous time random walk model. For cases when the jump length distribution is super-exponential, e.g., a Gaussian, we use large deviations theory and relate it to the appearance of exponential tails. When the jump length distribution is sub-exponential, the packet of spreading particles is described by the big jump principle. We demonstrate the applicability of our approach for finite time, indicating that rare events and the asymptotics of the large deviations rate function can be sampled for large length scales within a reasonably short measurement time.

The universality of Laplace tails appears everywhere

We study a multi-agent model of language dynamics that incorporates diffusion of linguistic traits and human dispersal, both influenced by local linguistic environment. We assume that each individual is characterized by a string, representing a language in terms of a set of linguistic features. Each individual can interact only with other individuals located within a finite neighborhood. The interaction between two individuals results in copying or passing a linguistic trait; the direction of the learning process is determined by the level of linguistic similarity with the neighborhood, estimated through the average Levenshtein distance. The latter determines also the diffusion coefficient of the random walk performed by the individuals. The dynamics of the model is investigated through numerical simulations over a wide range of parameters. Our results show a rich variety of possible final scenarios, ranging from language segregation and dialects formation to linguistic continua and consensus. The obtained language size distribution, spatial distribution of languages, and the correlation between geographic and linguistic distance at equilibrium resemble well the results observed in real systems.

The model dynamics incorporates diffusion of linguistic traits and human dispersal, both influenced by the local linguistic environment, in the spirit of the Axelrod and Shelling model, respectively. The system can reach different final scenarios ranging from consensus to fragmentation, like the equilibrium configuration shown that shows self-organized clusters: different symbols correspond to different languages (strings in the dendrogram) and each color represents a different dialect defined by the group emerging from the clustering analysis

The rigorous formulations of boson (the ideal Bose gas) and fermion-pair Bose–Einstein (BE) condensations reveal that the two condensed states are different; the boson condensation given by the boson coherent state is a sound condensed state based on a large number of states corresponding to the grand canonical ensemble of the classical ideal gas (average particle number N) where the norm of the coherent state is equivalent to the grand (canonical) partition function (Xi _{0}=e^{N}) of the latter. The fermion-pair condensation is a very limited condensed state formed between holes and fermion-pairs and its condensate is a fermion-pair and hole condensate. The singlet-bond (SB) superconductivity theory for cuprate high-temperature superconductors finds the following; (1) the superconducting transition is a first-order transition, (2) the experimentally observed exponential behavior of the specific heat coefficient (gamma (T)equiv C(T)/T) near (T_{c}) is caused by the high energy excitations of superconducting SB-pairs to the normal-state insulating immobile SB-pairs beyond the characteristic energy scale (sim k_{B}T_{c}) of the condensation energy, which is the same origin as that of the exponential (gamma (T)) behavior in the BCS superconductivity, and (3) Josephson tunneling in d-wave superconductor Josephson junction cannot give rise to the so-called (pi )-shift Josephson phase in both the underdoped and overdoped cuprate superconductor Josephson junctions.

This study utilized molecular dynamics simulations to explore the collective behavior of the two-dimensional self-propelled particles known as the inchworm particles, which are characterized by periodic variations in internal structure and driving force. Our primary objective is to elucidate the influence of the particle’s motion mode on pressure. We established a state equation for pressure derived from the observed motion mode and observed that inchworm-type particles exhibit distinct high-temperature characteristics in the pressure–temperature curve, unlike spherical self-propelled particles. Notably, their active pressure does not entirely diminish with increasing temperature. Distinct variations in the behavior of self-propelled particles across different sizes are identified. The findings contribute a more intricate model for the internal structure of self-propelled particles, offering valuable insights into this research area.

Many slow-fast systems can exhibit delayed bifurcation, which means that the crucial transition occurs after some delay during the transition between the oscillatory and steady states due to the presence of a slowly varying parameter. We specifically analyze the dynamical behavior of bifurcation delay in a network of nonlocally coupled FitzHugh–Nagumo neurons by adjusting the frequency of slowly varying currents. Interestingly, we observe an appearance of chimera-like states despite a tiny parameter mismatch in the frequency of any single node. The observed chimera-like state is evidenced through the mean-phase velocity profile. The robustness of the obtained results is then tested by perturbing multiple neurons in three different ways: constant, linearly increasing, and decreasing frequency of certain nodes. Importantly, we discover that the observed chimera state is resilient to all perturbations.