The European Physical Journal B最新文献

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.

Blending ordering within an uncorrelated disorder potential in families of 3D Lieb lattices preserves the macroscopic degeneracy of compact localized states and yields unconventional combinations of localized and delocalized phases—as shown in Liu et al. (Phys Rev B 106:214204, 2022). We proceed to reintroduce translation invariance in the system by further ordering the disorder, and discuss the spectral structure and eigenstates features of the resulting perturbed lattices. We restore order in steps by first (i) rendering the disorder binary—i.e., yielding a randomized checkerboard potential, then (ii) reordering the randomized checkerboard into an ordered one, and at last (iii) realigning all the checkerboard values yielding a constant potential shift, but only on a sub-lattice. Along this path, we test the influence of additional random impurities on the order restoration. We find that in each of these steps, about half of the dispersive states are projected upon the unperturbed sites hosting the degenerate compact states, while the remaining ones are localized in the perturbed sites with energy determined by the strength of checkerboard. This strategy, herewith implemented in the 3D Lieb lattice, highlights order restoration as experimental pathway to engineer spectral and states features in disordered lattice structures in the pursuit of quantum storage and memory applications.

The mesoscopic transport through double-quantum-dot (DQD) Aharonov–Bohm (AB) interferometer coupled with Majorana bound states (MBSs), as well as normal and superconductive terminals has been investigated. The current, shot noise and Fano factor have been calculated versus AB phase and source-drain bias (eV). The calculated Fano factor F displays explicit features of MBSs through its AB oscillations and source-drain bias characteristics. The sinusoid and multi-peak (4pi )-periodic oscillations are exhibited versus AB phase due to modifying the DQD levels and coupling constants. Significant peak-valley structures of Fano factor contributed by Andreev reflections and MBSs exhibit in small source-drain bias region. The Fano factor is suppressed by increasing the coupling strengths (lambda _i) (( i=1,2)) of MBSs with DQD, while it is enhanced by increasing the coupling energy ((varepsilon _{M})) between two MBSs. For the case as (varepsilon _{M}ne 0), a specific value around (Fapprox 2) is reached for different (lambda _i) as (eVrightarrow 0). While for the case as (varepsilon _{M}=0), small values around (Fapprox 0) are presented due to setting different coupling constants (lambda _i) as (eVrightarrow 0).

Using the mean field approximation based on the Bogoliubov inequality for free energy, we investigate the effects of the biquadratic exchange interaction on the critical behavior and phase diagram of the mixed spin (1,2) Blume–Emery–Griffiths model. We first focus on a specific case of the model: when the interaction parameter (K=0), corresponding to the Blume–Capel model. For the attractive Blume–Emery–Griffiths model, we present the phase diagram in the temperature-crystal field plane. The phase diagram is significantly influenced by the value of the biquadratic exchange interaction K. For small values of K, similar to the Blume–Capel model, the phase diagram exhibits first and second order phase transition lines separating ordered and disordered phases, with a tricritical point marking the boundary between these regions. As K increases, the phase diagram changes significantly, with the appearance of reentrant and double reentrant phenomena.

We have studied theoretically the magnetization M and the band gap energy (E_g) in dependence on temperature, size and ion doping concentration in the double perovskite La(_2)NiMnO(_6) (LNMO)—bulk and nanoparticles. LNMO is a ferromagnetic semiconductor. Therefore, it is appropriate to use for describing its properties the (s-d(f)) model. The method for the calculation of M and (E_g) is the Green’s function theory within we are able to make a finite temperature analysis of the excitation spectrum and of all physical quantities. The temperature-dependent Matsubara Green’s function formalism can be used for describing the temperature-dependent behavior of realistic systems in thermal equilibrium. M increases with decreasing the nanoparticle size. (E_g) decreases with increasing temperature. For nanoparticles, it is smaller than that of bulk LNMO. Doping with Sr ions at the La site reduces M and enhances (E_g). The band gap decreases by Sc ion doping at the La site. The substitution with different ions at the Ni site can also tune (E_g). For example, doping with Fe or Sc ion increases (E_g), whereas by Co, doping (E_g) decreases. Substitution by the same ion at different sites, A or B (La or Ni) leads to different behavior of the band gap. It is shown that Sr-, Ba-, Ca-, and Y-doped LNMO NPs with a band gap of (sim ) 1.4 eV are appropriate for application in solar cells. Comparison to the existing experimental data is made.

We study the dynamics of a single spin coupled to a bosonic bath at zero temperature driven by a ramp of the bias field. A single spin coupled to a bosonic sub-Ohmic bath exhibits a quantum phase transition at a certain strength of spin-boson coupling. When the bias field is ramped from a large value to zero at this critical coupling strength, the system initialized at the ground state ends up with a finite magnetization due to the critical slowing down near the transition. On the basis of the pulse-impulse approximation, we derive a scaling law between the residual magnetization and the ramp speed. The obtained scaling relation is examined using a numerical simulation based on the tensor network. The data are in favor of the scaling law to hold. We discuss the demonstration of our theoretical results by means of quantum simulation using the quantum annealer.