The European Physical Journal B最新文献

Biological information processing pathways in neuron assemblies rely on spike activity, encoding information in the time domain, and operating the highly parallel network at an outstanding robustness and efficiency. One particularly important aspect is the distributed, local pre-processing effectively converting stimulus-induced signals to action potentials, temporally encoding analog information. The field of brain-inspired electronics strives to adapt concepts of information processing in neural networks, e.g., stimulus detection and processing being intertwined. As such, stimulus-modulated resistive switching in memristive devices attracts an increasing attention. This work reports on a three-component memsensor circuit, featuring a UV-sensor, a memristive device with diffusive switching characteristics and a capacitor. Upon application of a DC bias, complex, stimulus-dependent spiking and brain-inspired bursting can be observed, as experimentally showcased using combination of a microstructured, tetrapodal ZnO sensor and a Au/SiO_xN_y/Ag cross-point memristive device. The experimental findings are corroborated by a wave digital model, which successfully replicates both types of behavior and outlines the relation of temporal variation of switching thresholds to the occurrence of bursting activity.

In addressing the complexity inherent in comparing socioeconomic indicators across diverse countries, a substantial barrier arises from the wide array of distinct calculation approaches. Consequently, a highly pertinent question emerges: how does one compare values when the underlying calculation methodologies are diverse? In this context, we propose a multidisciplinary and heterogeneous approach, employing numerical and visual comparisons to analyze socioeconomic indicators of municipalities in the US, Brazil and other Latin American countries. We identify independent-scale patterns in three stages: initially, by compiling a database sourced from respected institutions in each country and identifying correlations within this dataset; next, by creating graphical representations using a binning methodology for scatter plots of the identified patterns; finally, by transforming the dispersions from the initial stage into graphs using a variant of the Gravitational Clustering Algorithm technique from astrophysics. We find significant relationships, specifically in the logarithmic relationship between Municipal HDI and population size. In some countries, global minima were identified, suggesting the existence of a critical population density at which municipalities above this threshold exhibit a positive and significant correlation with an increase in their HDI.

We theoretically investigate spin photo-currents in two types of antiferromagnetic insulators with Dzyaloshinskii–Moriya (DM) interactions: one with staggered DM interactions and the other with uniform DM interactions. The magnon spectrum for each system thus becomes asymmetric with respect to the propagation direction of magnons, which may be utilized to enhance the nonlinear spin conductivity. Indeed, we show that the spin conductivity in each system could be up to the order of 10 nJ/((textrm{cm}^2cdot textrm{T}^2)) when the system is coupled to an AC magnetic field transverse to the ordered spins. Due to the special magnon dispersion, however, an extra static field is required to achieve a high conductivity in the system with staggered DM interactions. The results could be useful in opto-spintronics based on magnetic excitations.

The concept of dynamical freezing is a phenomenon where a suitable set of local observables freezes under a strong periodic drive in a quantum many-body system. This happens because of the emergence of approximate but perpetual conservation laws when the drive is strong enough. In this work, we probe the resilience of dynamical freezing to random perturbations added to the relative phases between the interfering states (elements of a natural basis) in the time-evolving wave function after each drive cycle. We study this in an integrable Ising chain in a time-periodic transverse field. Our key finding is, that the imprinted phase noise melts the dynamically frozen state, but the decay is “slow”: a stretched-exponential decay rather than an exponential one. Stretched-exponential decays (also known as Kohlrausch relaxation) are usually expected in complex systems with time-scale hierarchies due to strong disorders or other inhomogeneities resulting in jamming, glassiness, or localization. Here we observe this in a simple translationally invariant system dynamically frozen under a periodic drive. Moreover, the melting here does not obliterate the entire memory of the initial state but leaves behind a steady remnant that depends on the initial conditions. This underscores the stability of dynamically frozen states.

Computational models of peer interaction, with or without networks, have been applied to opinion dynamics to describe social phenomena. Here, we use the Deffuant–Weisbuch (DW) model of opinion dynamics, where a confidence parameter bounds individuals’ interactions, both in paradigmatic artificial networks and some social networks. The interaction of an individual with their immediate neighbors is incorporated into the model using Asch’s concept of social conformity. In general, conformity facilitates consensus in networks by reducing the time required to reach a state of equilibrium and by increasing the likelihood of a single opinion value prevailing throughout the network. In real networks, a higher probability of adherence ((p_{Asch}=0.6)) to the majority opinion increases the proportion of individuals in consensus within less tolerant networks ((d<0.5)). Conformity leads to more nodes agreeing around the same average opinion in a shorter time.

When at equilibrium, large-scale systems obey conventional thermodynamics because they belong to microscopic configurations (or states) that are typical. Crucially, the typical states usually represent only a small fraction of the total number of possible states, and yet the characterization of the set of typical states—the typical set—alone is sufficient to describe the macroscopic behavior of a given system. Consequently, the concept of typicality, and the associated Asymptotic Equipartition Property allow for a drastic reduction of the degrees of freedom needed for system’s statistical description. The mathematical rationale for such a simplification in the description is due to the phenomenon of concentration of measure. The later emerges for equilibrium configurations thanks to very strict constraints on the underlying dynamics, such as weekly interacting and (almost) independent system constituents. The question naturally arises as to whether the concentration of measure and related typicality considerations can be extended and applied to more general complex systems, and if so, what mathematical structure can be expected in the ensuing generalized thermodynamics. In this paper, we illustrate the relevance of the concept of typicality in the toy model context of the “thermalized” coin and show how this leads naturally to Shannon entropy. We also show an intriguing connection: The characterization of typical sets in terms of Rényi and Tsallis entropies naturally leads to the free energy and partition function, respectively, and makes their relationship explicit. Finally, we propose potential ways to generalize the concept of typicality to systems where the standard microscopic assumptions do not hold.