Irreversibility and spontaneous appearance of coherent behavior in reversible systems

There is empirical evidence that long time numerical simulations of conservative and reversible partial differential equations evolve, as a general rule (exceptions are the integrable models), towards an equilibrium state that is mainly a coherent structure plus small fluctuations inherent in the conservative and reversible character of the original system. The fluctuations account for the energy difference between the initial configuration and the one of the coherent structure. If the energy is not small enough, then the intrinsic fluctuations may destroy the coherent structure. Thus we arrive to the conclusion that a transition arises from a non-coherent state to a coherent structure as we decrease the initial energy below a critical value. This phenomenon has been successfully observed in various numerical simulations. In this article, we stress that this general behavior is also observed in reversible and conservative cellular automata as in the Q2R model. We point out that this conservative and reversible cellular automata is ab initio deterministic and therefore all our numerical computations are not affected by an approximation of any kind.     

Intractable problems in reversible cellular automata

The billiard ball model, a classical mechanical system in which all parameters are real variables, can perform all digital computations. An eight-state, 11-neighbor reversible cellular automaton (an entirely discrete system in which all parameters are integer variables) can simulate this model. One of the natural problems for this system is to determine the shape of a container so that the initial specific distribution of gas molecules eventually leads to a predetermined distribution. This problem is PSPACE-complete. Related intractable and decidable problems are discussed as well.     

A Three State Hard-Core Model on a Cayley Tree

Abstract

We consider a nearest-neighbor hard-core model, with three states , on a homogeneous Cayley tree of order k (with k + 1 neighbors). This model arises as a simple example of a loss network with nearest-neighbor exclusion. The state σ(x) at each node x of the Cayley tree can be 0, 1 and 2. We have Poisson flow of calls of rate λ at each site x, each call has an exponential duration of mean 1. If a call finds the node in state 1 or 2 it is lost. If it finds the node in state 0 then things depend on the state of the neighboring sites. If all neighbors are in state 0, the call is accepted and the state of the node becomes 1 or 2 with equal probability 1/2. If at least one neighbor is in state 1, and there is no neighbor in state 2 then the state of the node becomes 1. If at least one neighbor is in state 2 the call is lost. We focus on ‘splitting’ Gibbs measures for this model, which are reversible equilibrium distributions for the above process. We prove that in this model, ? λ > 0 and k ≥ 1, there exists a unique translationinvariant splitting Gibbs measure ^*. We also study periodic splitting Gibbs measures and show that the above model admits only translation - invariant and periodic with period two (chess-board) Gibbs measures. We discuss some open problems and state several related conjectures.     

Zigzag型边界石墨烯纳米带的电子态

在紧束缚近似下, 提出有限系统的Bloch定理方法, 解析计算了Zigzag型石墨烯纳米带的电子态和能带.研究发现, 其电子态有两类, 分别是驻波态和边缘态; 驻波态的波矢为实数, 波函数是正弦函数形式; 边缘态的波矢主要是虚数, 实数部分为零或者π/2, 波函数是双曲正弦函数形式. Zigzag型石墨烯纳米带的能带由驻波态能量和边缘态能量组成, 我们推导了边缘态的关于无限长方向波矢和能量的精确取值范围. 讨论了边缘态和驻波态的过渡点, 发现两种电子态通过不同的方式在受限波矢趋于零时关于格点位置逼近线性关系. 当受限方向也变成无限长时, 可以得到与无限大石墨烯相同的能带关系. 关键词： 紧束缚模型 Zigzag型石墨烯纳米带 边缘态     

Self-organized model of cascade spreading

We study simultaneous price drops of real stocks and show that for high drop thresholds they follow a power-law distribution. To reproduce these collective downturns, we propose a minimal self-organized model of cascade spreading based on a probabilistic response of the system elements to stress conditions. This model is solvable using the theory of branching processes and the mean-field approximation. For a wide range of parameters, the system is in a critical state and displays a power-law cascade-size distribution similar to the empirically observed one. We further generalize the model to reproduce volatility clustering and other observed properties of real stocks.     

The role of defects in the formation of the multidomain state of easy-plane antiferromagnets with magnetoelastic interaction

We analyzed the field dependences of forced magnetostriction in the multidomain state of the easy-plane antiferromagnet CoCl₂ obtained in the following cycles: the introduction-removal of a magnetic field lying in the easy plane, the introduction-removal of a magnetic field lying in the easy plane and directed normally to that introduced earlier, etc. The magnetostriction of the crystal in the multidomain state was shown to contain two components. First, the component reversible in the cycle magnetic field introduction-removal, which makes the major contribution in the crystal under consideration, and, second, a comparatively small irreversible component, that is, the contribution retained after magnetic field removal. In low fields, the reversible magnetostriction component was proportional to the square of the applied magnetic field. Field-induced rearrangement of the multidomain antiferromagnetic state was found to be responsible for singularities of the field dependence of crystal magnetization. In particular, in a near-zero field that lay in the easy plane, the transverse susceptibility decreased twofold compared with its value in fields in which the crystal is already in the monodomain state. At the same time, close to the “monodomainization” field, transverse magnetic susceptibility was maximum. Defects were shown to favor the formation of the reversible multidomain state. Determining factors in this process were elastic and magnetoelastic interactions. The multidomain state of antiferromagnets was described using the domain distribution function over the orientations of domain antiferromagnetic vectors with respect to the magnetic field direction and the magnetic field dependence of this function. The results of our analysis were in close agreement with the experimental data on CoCl₂.     

Classical and quantum limitations on energy consumption in computation

Fundamental limitations on the energy dissipated during one elementary logical operation are discussed. A model of a real physical device (parametric quantron) based on the Josephson effect in superconductors is used throughout the discussion. This device is shown to be physically reversible, and moreover it can serve as the clementary cell of a logically reversible computer, both these properties being necessary to achieve the fundamental limits of energy dissipation. These limits due to classical and quantum statistics are shown to lie well below the earlier estimates,k _B T and , respectively.     

Control of epileptiform spikes based on nonlinear unscented Kalman filter

A new control strategy based on nonlinear unscented Kalman filter(UKF) is proposed for a neural mass model that serves as a model for simulating real epileptiform stereo-electroencephalographic (SEEG) signals. The UKF is used as an observer to estimate the state from the noisy measurement because it has been proved to be effective for state estimation of nonlinear systems. A UKF controller is constructed via the estimated state and is illustrated to be effective for epileptiform spikes suppression of aforementioned model by numerical simulations.     

Bistability in a superconducting Al thin film induced by arrays of Fe-nanodot magnetic vortices

A hybrid system, consisting of an array of Fe nanodots covered by a superconducting Al thin film, exhibits very unusual magnetotransport, including a giant hysteretic magnetoresistance with different reversible or irreversible regimes related to the magnetic state of the array. These effects originate from the magnetic fields produced by magnetic nanodots in the "magnetic vortex state." This is a unique model system in which properties of a magnetic array are transferred into the superconductor.     

A model of the effects of authority on consensus formation in adaptive networks: Impact on network topology and robustness

Opinions of individuals in real social networks are arguably strongly influenced by external determinants, such as the opinions of those perceived to have the highest levels of authority. In order to model this, we have extended an existing model of consensus formation in an adaptive network by the introduction of a parameter representing each agent’s level of ‘authority’, based on their opinion relative to the overall opinion distribution. We found that introducing this model, along with a randomly varying opinion convergence factor, significantly impacts the final state of converged opinions and the number of interactions required to reach that state. We also determined the relationship between initial and final network topologies for this model, and whether the final topology is robust to node removals. Our results indicate firstly that the process of consensus formation with a model of authority consistently transforms the network from an arbitrary initial topology to one with distinct measurements in mean shortest path, clustering coefficient, and degree distribution. Secondly, we found that subsequent to the consensus formation process, the mean shortest path and clustering coefficient are less affected by both random and targeted node disconnection. Speculation on the relevance of these results to real world applications is provided.     

Remarks on entropy and irreversibility in non-hamiltonian systems

Entropy and irreversibility in non-hamiltonian systems are discussed from a fully covariant point of view. The discussion is based on the generalized Liouville equation, the definition of a volume element dV in state space, and a generalized hypothesis of equal a priori probabilities. Systems may be classified as reversible or irreversible according to whether it is or is not possible to define dV so that the flow is globally volume-preserving in state space.     

Modeling the capability of penetrating a jammed crowd to eliminate freezing transition

Frozen state from jammed state is one of the most interesting aspects produced when simulating the multidirectional pedestrian flow of high density crowds. Cases of real life situations for such a phenomenon are not exhaustively treated.Our observations in the Hajj crowd show that freezing transition does not occur very often. On the contrary, penetrating a jammed crowd is a common aspect. We believe the kindness of pedestrians facing others whose walking is blocked is a main factor in eliminating the frozen state as well as in relieving the jammed state. We refine the social force model by incorporating a new social force to enable the simulated pedestrians to mimic the real behavior observed in the Hajj area.Simulations are performed to validate the work qualitatively.     

Large-angle 6Li + 28Si elastic and inelastic scattering at 27 and 34 MeV

Elastic and inelastic scattering data extending to θ_c.m ≈ 175° are reported for ⁶Li + ²⁸Si at 27 and 34 MeV. Optical model analyses of the elastic data were made using a variety of real potential forms. The large-angle data cannot be fitted with a Woods-Saxon real potential, but are well described by Woods-Saxon squared, double-folded or Fourier-Bessel potentials. The real potential is the same at both energies, but the imaginary potential is weaker at 27 MeV. The inelastic data were analyzed using the DWBA and coupled channels techniques with folded real form factors and deformed Woods-Saxon imaginary potentials, with the deformations taken from electron scattering. The 2⁺ state was fitted well at both energies with the DWBA, while the prediction decreased too rapidly at large angles for the 4⁺ state. The large-angle 4⁺ data were better described when two-step excitations were included in the coupled-channels calculations. The forward-angle 2⁺ data are sensitive to the interference between Coulomb and nuclear scattering and show that the nuclear and Coulomb deformation parameters β₂ are equal for this transition.     

Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter

Data assimilation is an iterative approach to the problem of estimating the state of a dynamical system using both current and past observations of the system together with a model for the system’s time evolution. Rather than solving the problem from scratch each time new observations become available, one uses the model to “forecast” the current state, using a prior state estimate (which incorporates information from past data) as the initial condition, then uses current data to correct the prior forecast to a current state estimate. This Bayesian approach is most effective when the uncertainty in both the observations and in the state estimate, as it evolves over time, are accurately quantified. In this article, we describe a practical method for data assimilation in large, spatiotemporally chaotic systems. The method is a type of “ensemble Kalman filter”, in which the state estimate and its approximate uncertainty are represented at any given time by an ensemble of system states. We discuss both the mathematical basis of this approach and its implementation; our primary emphasis is on ease of use and computational speed rather than improving accuracy over previously published approaches to ensemble Kalman filtering. We include some numerical results demonstrating the efficiency and accuracy of our implementation for assimilating real atmospheric data with the global forecast model used by the US National Weather Service.     

A two-dimensional Heisenberg <Emphasis Type="Italic">S</Emphasis> = 1 antiferromagnet with exchange interactions of two types on a hexagonal lattice: RSRG and DMRG analyses

An anisotropic Heisenberg spin S = 1 model on a two-dimensional hexagonal lattice (formed from interacting chains) with antiferromagnetic nearest-neighbor interactions of two types is analyzed by the real space renormalization group method. The problem of the influence of interchain pairing on the critical properties of the model is studied, and the phase diagram of the model is constructed. The two-dimensional density matrix renormalization group algorithm is used to calculate the ground state energy for the isotropic case as a function of the ratio between interchain and intrachain interactions.     

Tunneling negative-U centers and photo-induced reactions in solids

A model of tunneling centers which acquire the negative-U value as a result of a dependence shown by the electron-vibration interaction constant upon the center charge state is proposed. We address the question whether the model is of a sufficiently general character to be applied to the investigation of the tunneling probabilities for centers due to the reversible rearrangements brought about in lattice defects by optical pumping, photo-induced reactions occurring in semiconductors and photochromic materials, and by adsorbate photodesorption. The tunneling systems of the type being considered have been observed in the experimentally investigated gold centers in silicon.     

基于不敏粒子滤波的水中非合作磁性目标实时磁定位方法

针对水中非合作磁性目标的实时定位问题, 提出了一种基于不敏粒子滤波(unscented particle filter, UPF)的实时磁定位方法. 从非合作磁性目标的运动特征出发, 建立了状态空间模型, 利用UPF算法对目标状态进行实时估计. 为了提高系统的可观测性, 在算法迭代过程中对粒子状态进行约束及利用最小二乘法反演磁矩. 仿真与铁磁物体定位实验结果表明, 该方法的定位精度较高, 实时定位效果较好, 可用于近场实时磁定位问题中. 关键词： 磁定位 椭球体模型 状态空间模型 不敏粒子滤波