International Journal of Modern Physics C

The possible existence of quantum crystals phase of polariton condensate in two-dimensional microcavity polariton was studied by using mean-field method for bosons at zero temperature. In this study, we observe the supersolid crystallized (hexagonal, square) and a quantized winding number of the phase in a regime of strong- field interaction in rotating exciton–polariton condensates. First, the ground state of the condensate was found; and the solution was further extended for dynamics state to reach the equilibrium steady-state as well as their density profile and energy diagrams. The supersolid crystal is the result of the considerable deviation induced by the interaction of polaritons of both ground and dynamic states of a dressed dipolar Bose–Einstein condensate. Here, the researchers demonstrated the formation of a hexagonal lattice in the nonlinear regime at high polariton-density where polariton–polariton interactions dominate the behavior of the system. It was identified that stability regimes for ground state increases as the polariton–polariton interaction strength increases. The phase diagram for the stable vortex state will be useful for conducting experimental and theoretical studies on rotating dipolar quantum gases and many other exotic systems.

Corrections to scaling in the 3D Ising model are studied based on nonperturbative analytical arguments and Monte Carlo (MC) simulation data for different lattice sizes $L$. Analytical arguments show the existence of corrections with the exponent $(\gamma -1)∕\nu \approx 0.38$, the leading correction-to-scaling exponent being $\omega \le (\gamma -1)∕\nu$. A numerical estimation of $\omega$ from the susceptibility data within $40\le L\le 2560$ yields $\omega =0.21(29)$, in agreement with this statement. We reconsider the MC estimation of $\omega$ from smaller lattice sizes, $L\le 384$, using different finite-size scaling methods, and show that these sizes are still too small, since no convergence to the same result is observed. In particular, estimates ranging from $\omega =0.866(21)$ to $\omega =1.247(73)$ are obtained, using MC data for thermodynamic average quantities, as well as for partition function zeros. However, a trend toward smaller $\omega$ values is observed in one of these cases in a refined estimation from extended data up to $L=1536$. We discuss the influence of $\omega$ on the estimation of critical exponents $\eta$ and $\nu$.

In this paper, an implicit-explicit finite-difference lattice Boltzmann method with subgrid model on nonuniform meshes is proposed. The implicit-explicit Runge–Kutta scheme, which has good convergence rate, is used for the time discretization and a mixed difference scheme, which combines the upwind scheme with the central scheme, is adopted for the space discretization. Meanwhile, the standard Smagorinsky subgrid model is incorporated into the finite-difference lattice Boltzmann scheme. The effects of implicit-explicit Runge–Kutta scheme and nonuniform meshes of present lattice Boltzmann method are discussed through simulations of a two-dimensional lid-driven cavity flow on nonuniform meshes. Moreover, the comparison simulations of the present method and multiple relaxation time lattice Boltzmann subgrid method are conducted qualitatively and quantitatively.

In this paper, a new car-following model considering effect of the driver’s forecast behavior is proposed based on the full velocity difference model (FVDM). Using the new model, we investigate the starting process of the vehicle motion under a traffic signal and find that the delay time of vehicle motion is reduced. Then the stability condition of the new model is derived and the modified Korteweg–de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Numerical simulation is compatible with the analysis of theory such as density wave, hysteresis loop, which shows that the new model is reasonable. The results show that considering the effect of driver’s forecast behavior can help to enhance the stability of traffic flow.

A thermal lattice Boltzmann equation (LBE) model within the framework of double distribution function (DDF) method is proposed from the continuous DDF Boltzmann equation, which has a clear physical significance. Since the discrete velocity set in present LBE model is not space filled, a Lax–Wendroff scheme is applied to solve the evolution equations by which the spatial interpolation of two distribution functions is overcome. To validate the model, some classical numerical tests include thermal Couette flow and natural convection flow are simulated, and the results agree well with the analytic solutions and other numerical results, which showed that the present model had the ability to describe the thermal fluid flow phenomena.

The carbon structures of phases A and B of methane are investigated through classical molecular dynamics simulations using optimized potentials for liquid simulations all-atom force fields as well as ReaxFF reactive force fields. Both final thermodynamic states were obtained by the proper ramping of temperature and pressure through well-known regions of methane’s phase diagram using the isothermal–isobaric (NPT) ensemble. Our calculated structures are in good agreement with very recent experimental data. The knowledge of these phases is the basis for the study of methane at high pressures.

A Green’s function formalism is used to calculate the spectrum of localized states associated with an interstitial magnetic impurity in a semi-infinite ferromagnet described by the transverse Ising model. The nonresonant and resonant excitations of the system due to the impurity (i.e. the defect modes outside and inside, respectively, the region of the bulk and surface spin waves (SW)) are calculated numerically for the high-temperature phase. Two situations are analyzed, depending on the position of the interstitial impurity: the impurity is in the surface ($N=1$) and the impurity is in the bulk region ($N>2$).

This paper is aimed at constructing robust multilayer networks against cascading failure. Considering link protection strategies in reality, we design a cascading failure model based on load distribution and extend it to multilayer. We use the cascading failure model to deduce the scale of the largest connected component after cascading failure, from which we can find that the performance of four kinds of load distribution strategies associates with the load ratio of the current edge to its adjacent edge. Coupling preference is a typical characteristic in multilayer networks which corresponds to the network robustness. The coupling preference of multilayer networks is divided into two forms: the coupling preference in layers and the coupling preference between layers. To analyze the relationship between the coupling preference and the multilayer network robustness, we design a construction algorithm to generate multilayer networks with different coupling preferences. Simulation results show that the load distribution based on the node betweenness performs the best. When the coupling coefficient in layers is zero, the scale-free network is the most robust. In the random network, the assortative coupling in layers is more robust than the disassortative coupling. For the coupling preference between layers, the assortative coupling between layers is more robust than the disassortative coupling both in the scale free network and the random network.

An epidemic spreading model is presented in the framework of the kinetic theory of active particles. The model is characterized by the influence of risk perception which can reduce the diffusion of infection. The evolution of the system is modeled through nonlinear interactions, whose output is described by stochastic games. The results of numerical simulations are discussed for different initial conditions.

We study the structural robustness of the scale free network against the cascading failure induced by overload. In this paper, a failure mechanism based on betweenness-degree ratio distribution is proposed. In the cascading failure model we built the initial load of an edge which is proportional to the node betweenness of its ends. During the edge random deletion, we find a phase transition. Then based on the phase transition, we divide the process of the cascading failure into two parts: the robust area and the vulnerable area, and define the corresponding indicator to measure the performance of the networks in both areas. From derivation, we find that the vulnerability of the network is determined by the distribution of betweenness-degree ratio. After that we use the connection between the node ability coefficient and distribution of betweenness-degree ratio to explain the cascading failure mechanism. In simulations, we verify the correctness of our derivations. By changing connecting preferences, we find scale free networks with a slight assortativity, which performs better both in robust area and vulnerable area.

As a significant problem in complex networks, link prediction aims to find the missing and future links between two unconnected nodes by estimating the existence likelihood of potential links. It plays an important role in understanding the evolution mechanism of networks and has broad applications in practice. In order to improve prediction performance, a variety of structural similarity-based methods that rely on different topological features have been put forward. As one topological feature, the path information between node pairs is utilized to calculate the node similarity. However, many path-dependent methods neglect the different contributions of paths for a pair of nodes. In this paper, a local weighted path (LWP) index is proposed to differentiate the contributions between paths. The LWP index considers the effect of the link degrees of intermediate links and the connectivity influence of intermediate nodes on paths to quantify the path weight in the prediction procedure. The experimental results on 12 real-world networks show that the LWP index outperforms other seven prediction baselines.

This paper deals with numerical modeling of two-phase liquid jet breakup using the smoothed particle hydrodynamics (SPH) method. Simulation of multiphase flows involving fluids with a high-density ratio causes large pressure gradients at the interface and subsequently divergence of numerical solutions. A modified procedure extended by Monaghan and Rafiee is employed to stabilize the sharp interface between the fluids. Various test cases such as Rayleigh–Taylor instability, two-phase still water and air bubble rising in water have been conducted, by which the capability of accurately capturing the physics of multiphase flows is verified. The results of these simulations are in a good agreement with analytical and previous numerical solutions. Finally, the simulation of the breakup process of liquid jet into surrounding air is accomplished. The whole numerical solutions are accomplished for both Wendland and cubic spline kernel functions and Wendland kernel function gave more accurate results. Length of liquid breakup in Rayleigh regime is calculated for various flow conditions such as different Reynolds and Weber numbers. The results of breakup length demonstrate in satisfactory agreement with the experimental correlation. Finally, impinging distance and breakup length of a simple multijet setup are analyzed. The two-jet multijet has a longer breakup length than a three-jet one.

In this paper, we present a simulator for two-particle quantum walks on the line and one-particle on a two-dimensional squared lattice. It can be used to investigate the equivalence between the two cases (one- and two-particle walks) for various boundary conditions (open, circular, reflecting, absorbing and their combinations). For the case of a single walker on a two-dimensional lattice, the simulator can also implement the Möbius strip. Furthermore, other topologies for the walker are also simulated by the proposed tool, like certain types of planar graphs with degree up to 4, by considering missing links over the lattice. The main purpose of the simulator is to study the genuinely quantum effects on the global properties of the two-particle joint probability distribution on the entanglement between the walkers/axis. For that purpose, the simulator is designed to compute various quantities such as: the entanglement and classical correlations, (classical and quantum) mutual information, the average distance between the two walkers, different hitting times and quantum discord. These quantities are of vital importance in designing possible algorithmic applications of quantum walks, namely in search, 3-SAT problems, etc. The simulator can also implement the static partial measurements of particle(s) positions and dynamic breaking of the links between certain nodes, both of which can be used to investigate the effects of decoherence on the walker(s). Finally, the simulator can be used to investigate the dynamic Anderson-like particle localization by varying the coin operators of certain nodes on the line/lattice. We also present some illustrative and relevant examples of one- and two-particle quantum walks in various scenarios. The tool was implemented in C and is available on-line at http://qwsim.weebly.com/.

A modified ghost fluid (MGF) method for reducing the spurious pressure oscillations in moving boundaries is proposed on the lattice Boltzmann method (LBM). The primary cause of these oscillations is the violation of the boundary geometric conservation law for sharp-interface immersed boundary. We introduce a simple weight strategy into GF method to strictly enforce geometric conservation. The weight strategy reduces the abrupt change of the distribution function on the boundary node when passing through the moving boundary. Some simulations are shown to test the validity of the method. The results illustrate that the modified method maintains the same validity as the GF and reduces the spurious pressure oscillations near the boundaries.