The European Physical Journal B最新文献

Chaotic Floquet systems at sufficiently low driving frequencies are known to heat up to an infinite temperature ensemble in the thermodynamic limit. However at high driving frequencies, Floquet systems remain energetically stable in a robust prethermal phase with exponentially long heating times. We propose sensitivity (susceptibility) of Floquet eigenstates against infinitesimal deformations of the drive, as a sharp and sensitive measure to detect this heating transition. It also captures various regimes (timescales) of Floquet thermalization accurately. Particularly, we find that at low frequencies near the onset of unbounded heating, Floquet eigenstates are maximally sensitive to perturbations and consequently the scaled susceptibility develops a sharp maximum. We further connect our results to the relaxation dynamics of local observables to show that near the onset of Floquet heating, the system is nonergodic with slow glassy dynamics despite being nonintegrable at all driving frequencies.

We consider a large population of (textit{M}) agents, who are randomly selected to form size-distributed groups from time to time, and the grouped agents engage in the Public Goods Game (PGG). The size (textit{g}) of the group is within (textit{g}_textit{l}) and (textit{g}_textit{h}), where (textit{g}_textit{l}) and (textit{g}_textit{h}) are the lower and upper limits of the group size, respectively. Players have two strategies to choose, i.e., to cooperate (C), or to defect (D). Based on the dynamic grouping, we investigate the cooperative behavior of the system, and the results show that the frequency of cooperation is greatly affected by the noise intensity and group size distribution. In the evolutionary process, the payoffs of the cooperators (defectors) mainly depend on the strategy selection implemented by the death-birth process. For (textit{g}in text {[1,3]}), different noise intensities (textit{K}) induce different dynamic behaviors together with the multiplication factor (textit{r}). For (textit{g}in text {[1,5]}), the system may evolve to one of the bistable states (one is the totally cooperative state and the other is a mixed state with cooperators and defectors) starting from different initial concentrations of cooperation. The results of numerical computation seems to fit well with the simulation data. Furthermore, for (K=1.0) and (g in [1,5]), we still observe the phenomenon of hysteresis effect where the system just reaches to the totally cooperative state slowly after a period of delay with increasing multiplication factor r. In addition, when one D-player tries to invade the C-population, there exists a critical game parameter (textit{r}_textit{invade}), below which the C-population will be invaded. We also study how the critical game parameter relies on the noise intensity and the group size distribution.

This work establishes the existence of dispersive nodal-arcs and their evolution into Weyl nodes under the effect of spin-orbit coupling (SOC) in NbAs and NbP. The obtained features mimic the observations as reported for TaAs and TaP in our previous work (Pandey in J Phys Condens Matter 35:455501, 2023). In addition, this work reports that the number of nodes in the TaAs class of Weyl semimetals (WSMs) can be altered by creating strain along a or c direction of the crystals. For instance, the number of nodes in NbAs under SOC-effect along with 2% (3%) tensile-strain in a direction is found to be 40 (56) in its full Brillouin zone (BZ). Besides the nodes, such strain are found to have considerable impact on the nodal-lines of these WSMs when effect of SOC is ignored. In the absence of SOC, a 3% tensile (compressive) strain along the a (c) direction leads to the partially merging of nodal-lines in the extended BZ of NbAs and NbP, which is not observed in TaAs and TaP within the range of – 3% to 3% strain. Apart from this, the work discusses the role of Weyl physics in affecting the Seebeck coefficient (S) of any WSM. In this direction, it is discussed that how a symmetric Weyl cone, even if tilted, will have no contribution to the S of WSMs. Furthermore, the work highlights the conditions under which a Weyl cone can contribute to the S of a given WSM. Next, the discussion of Weyl contribution to S is validated over TaAs class of WSMs via investigating the features of their Weyl cones and calculating the contributions of such cones to the S of these semimetals. Weyl-cone contributed S in these WSMs is found to be anisotropic within the temperature range of 0–100 K. The value of S contributed from Weyl cone is found to be as large as (sim )70 (mu )V/K below 25 K in case of NbP. Lastly, the expected effect of axial strain and change in SOC-strength on S of TaAs class of WSMs is discussed. The findings of this work present a possibility of engineering the topological properties of TaAs class of WSMs via creating strain in their crystal. It also makes the picture of Weyl physics’  impact on the S of WSMs a more clear.

We present a novel method for analyzing the structural organization of protein families by integrating random matrix theory (RMT) and network theory with the physiochemical properties of amino acids and multiple sequence alignment. RMT distinguishes significant interactions between amino acids from background noise, pinpointing coevolving positions likely crucial for protein structure and function. This property-based approach captures both short and long-range correlations, unlike previous methods that treat amino acids as mere characters. The eigenvector components of eigenvalues outside the RMT bound deviate from typical RMT observations, offering critical system information. We quantify the information content of each eigenvector using an entropic estimate, showing that the smallest eigenvectors are highly localized and informative. These eigenvectors form clusters of biologically and structurally significant positions, validated by experiments. By creating networks of amino acid interactions for each property, we uncover key motifs and interactions. This method enhances our understanding of protein evolution, interactions, and potential targets to modulate enzymatic actions. We study two protein families Cadherin-4 and Betalactamase families which display two extreme characteristics one nearly random and the other very structured or organised.

The square-lattice (J_1)-(J_2) XXZ model with the ring-exchange interaction K was investigated numerically. As for the hard-core-boson model with the nearest-neighbor hopping (J_1/2), namely, the (J_1)-K XY model, it has been reported that the ring exchange leads to a variety of exotic phases such as the valence-bond-solid (VBS) phase. In this paper, we extend the parameter space to investigate the phase boundary between the XY (superfluid) and VBS phases. A notable feature is that the phase boundary terminates at the fully frustrated point, (J_2/J_1 rightarrow 0.5^-). As a scaling parameter for the multi-criticality, the distance from the multi-critical point (delta (ge 0)) is introduced. To detect the phase transition, we employed the high-order fidelity susceptibility (chi ^{(3)}_F), which is readily evaluated via the exact-diagonalization scheme. As a demonstration, for a fixed value of (delta ), the XY-VBS criticality was analyzed by the probe (chi ^{(3)}_F). Thereby, with properly scaling (delta ), the (chi ^{(3)}_F) data were cast into the crossover-scaling formula to determine the multi-criticality.

We propose a method that can generate customer trajectories and purchasing behaviors in retail stores simultaneously using Transformer-based deep learning structure. Utilizing customer trajectory data, layout diagrams, and retail scanner data obtained from a retail store, we trained a GPT-2 architecture from scratch to generate indoor trajectories and purchase actions. Additionally, we explored the effectiveness of fine-tuning the pre-trained model with data from another store. Results demonstrate that our method reproduces in-store trajectories and purchase behaviors more accurately than LSTM and SVM models, with fine-tuning significantly reducing the required training data.

With the popularity of social media, the speed and scale of information dissemination has increased exponentially, among which rumors have become a prominent issue that arouses public concern. Due to the lack of comprehensive consideration of population flow, propagation mechanisms, and effective rumor refutation strategies, as well as related dynamical analysis in traditional models, we propose an extended ISR rumor spreading model based on the traditional SIR (Susceptible, Infected, Recovered) model. The average field equation is established by introducing the flow of population, trust and suspicion mechanism and two rumor-refuting strategies, and the basic reproduction number of homogeneous and heterogeneous networks and the stability of the rumor-free equilibrium point are analyzed. Finally, our experimental simulation shows that the trust mechanism increases the speed and scale of the spread of rumors in the network, while the suspicion mechanism inhibits the spread of rumors and gradually reduces the spread scale. In addition, the dual rumor refutation strategy has a good inhibition effect on the spread of rumors, especially the direct rumor refutation by the disseminator, and has been verified in different models. These findings enhance our understanding of rumor dynamics and suggest strategies for mitigating misinformation in social networks.

Here, we show that the ferro(para)magnetic and non-collinear antiferromagnetic interfaces contribute to oscillating signals observed in the magnetoresistance. We associate the effect with the fact that the spins on the surface of IrMn(_3) produce instability in the surface magnetoresistance of the material, which is sensitive to the magnetic field. We carried out experiments using bilayers of IrMn(_3) under permalloy (Py) and IrMn(_3) under platinum (Pt). The oscillations were intensely evident at the Py/IrMn(_3) interface and less explicit at the Pt/IrMn(_3) interface. We carried out the experiments using pulsed current, with a square pulse width of 1 (mu )s and amplitudes of (I_{AC}) = 20 (mu )A to 20 mA. The oscillating signals are proportional to the crystallographic direction of the material, the ferromagnetism of the material adjacent to IrMn(_3), and sensitive to the amplitude of the pulsed current. We believe that observation is a way of transmitting encoded information through magnetoresistance.