Asymptotic behavior of fluctuations for the 1D Ising model in zero-temperature limit

Fluctuation of the average spin for one-dimensional Ising spins with nearest neighbor interactions are studied. The distribution function for the average spin is calculated for a finite volume, finite temperature, and finite magnetic field. As the volume increases and the temperature diminishes at zero magnetic field, there are two limits in which the probability distribution shows quite different behaviors: in the thermodynamic limit as the volume goes to infinity for finite temperature, small deviations of the fluctuations are described by a Gaussian distribution, and in the limit as the temperature vanishes for a finite volume, the ground states are realized with probability one. The crossover between these limits is analyzed via a ratio of the correlation length to the volume. The helix-coil transition in a polypeptide is discussed as an application.     

行列可交换不相关随机变量组列的中心极限定理之收敛速度

（ｘｉｊ）为行列可交换不相关随机变量组列,本文讨论ｓｕｐ│ｐ（ａ＾－１ｎＴｎ〈ｘ）－Φ（ｘ）│→０的速度（其中Ｔｎ＝１／ｎ２ｎΣｉ＝１ｎΣｊ＝１ｘｉｊ,Ｏ＾２ｎ＝ＶａｒＴｎ,Φ（ｘ）为标准正态分布函数）,取得了与Ｕ－统计量情形下相同的结果。     

独立随机变量部分和的大偏差概率的估计

设｛Ｘｎ｝ｎ≥１是一列相互独立且具有相同分布、非负非退化的随机变量序列．Ｓ＝Ｘ１＋…＋Ｘｎ，μＥＸ１，ａ是Ｘ１的分布支撑的上确界．假设ＥｅｕＸ１＜∞，ｕ＞０．对μ＜Ｘｎ＜ａ，本文分别讨论了１ｏｇＰ｛Ｓｎ≥ｎｘｎ｝及Ｐ｛Ｓｎ≥ｎｘｎ｝Ｊ当ｎ→∞时的渐近性质。     

非自治动力系统中周期跟踪和极限跟踪的研究

根据自治动力系统中周期跟踪性和极限跟踪性的定义,将其引入到非自治动力系统。研究了非自治动力系统中周期跟踪性和极限跟踪性的动力学性质,得到：(1)若F={fi}i=0∞拓扑共轭于G={gi}i=0∞,则F具有周期跟踪性当且仅当G具有周期跟踪性;(2)若F={fi}i=0∞拓扑共轭于G={gi}i=0∞,则F具有极限跟踪性当且仅当G具有极限跟踪性;(3)若乘积系统(X×Y,F×G)具有周期跟踪性,则(X,F)和(Y,G)具有周期跟踪性。 以上结论对非自治动力系统中跟踪性的发展有一定的促进作用。     

The Quantum-Classical Comparison of the Arrival-Time Distribution Through the Probability Current

We consider the arrival time distribution defined through the quantum probability current for a Gaussian wave packet representing free particles in quantum mechanics in order to explore the issue of the classical limit of arrival time. We formulate the classical analogue of the arrival time distribution for an ensemble of free particles represented by a phase space distribution function evolving under the classical Liouville's equation. The classical probability current so constructed matches with the quantum probability current in the limit of minimum uncertainty. Further, it is possible to show in general that smooth transitions from the quantum mechanical probability current and the mean arrival time to their respective classical values are obtained in the limit of large mass of the particles.     

The Chemical Potential

The definition of the fundamental quantity, the chemical potential, is badly confused in the literature: there are at least three distinct definitions in various books and papers. While they all give the same result in the thermodynamic limit, major differences between them can occur for finite systems, in anomalous cases even for finite systems as large as a cm³. We resolve the situation by arguing that the chemical potential defined as the symbol μ conventionally appearing in the grand canonical density operator is the uniquely correct definition valid for all finite systems, the grand canonical ensemble being the only one of the various ensembles usually discussed (microcanonical, canonical, Gibbs, grand canonical) that is appropriate for statistical thermodynamics, whenever the chemical potential is physically relevant. The zero–temperature limit of this μ was derived by Perdew et al. for finite systems involving electrons, generally allowing for electron–electron interactions; we extend this derivation and, for semiconductors, we also consider the zero–T limit taken after the thermodynamic limit. The enormous finite size corrections (in macroscopic samples, e.g. 1 cm³) for one rather common definition of the c.p., found recently by Shegelski within the standard effective mass model of an ideal intrinsic semiconductor, are discussed. Also, two very–small–system examples are given, including a quantum dot.     

Chaotic Dynamics in an Electronic Model of a Genetic Network

We consider dynamics in a class of piecewise-linear ordinary differential equations and in an electronic circuit that model genetic networks. In these models, gene activity varies continuously in time. However, as in Boolean or discrete-time switching networks, gene activity is driven high or low based only on whether the activities of the regulating genes are high or low (i.e., above or below certain thresholds). Depending on the “regulatory logic”, these models can exhibit simple dynamics, like stable fixed points or oscillation, or chaotic dynamics. The observed qualitative and quantitative differences between the dynamics in the idealized equations and the dynamics in the electronic circuit lead us to focus attention on the analysis of the dynamics as a function of parameter values. We propose new techniques for solving the inverse problem – the problem of inferring the regulatory logic and parameters from time series data. We also give new symbolic and statistical methods for characterizing dynamics in these networks.     

The Stationary Nonlinear Boltzmann Equation in a Couette Setting with Multiple, Isolated L q -solutions and Hydrodynamic Limits

This paper studies the stationary nonlinear Boltzmann equation for hard forces, in a Couette setting between two coaxial, rotating cylinders with given indata of Maxwellian type on the cylinders. A priori estimates are obtained mainly in L², leading to multiple, isolated solutions together with a hydrodynamic limit control, based on asymptotic expansions together with a rest term.     

Optimizing thermography depth probing with a dynamic thermal point spread function

Derivation of two point spread functions PSFs suitable for infrared thermograms analysis is illustrated, based on two unique approaches, one based on depth decaying limit and one on diffusion limit. Experimental work using PMMA sample with back drilled holes and pulsed thermographic routine is utilized to show the effectiveness of deconvoluting pixel temperature transient history with suggested PSF’s. Synthetic second time derivative thermograms are utilized for comparison and the signal to noise ratio is used as a figure of merit for quantification.     

Three-step approach for prediction of limit cycle pressure oscillations in combustion chambers of gas turbines

Currently, gas turbine manufacturers frequently face the problem of strong acoustic combustion driven oscillations inside combustion chambers. These combustion instabilities can cause extensive wear and sometimes even catastrophic damages to combustion hardware. This requires prevention of combustion instabilities, which, in turn, requires reliable and fast predictive tools. This work presents a three-step method to find stability margins within which gas turbines can be operated without going into self-excited pressure oscillations. As a first step, a set of unsteady Reynolds-averaged Navier–Stokes simulations with the Flame Speed Closure (FSC) model implemented in the OpenFOAM® environment are performed to obtain the flame describing function of the combustor set-up. The standard FSC model is extended in this work to take into account the combined effect of strain and heat losses on the flame. As a second step, a linear three-time-lag-distributed model for a perfectly premixed swirl-stabilized flame is extended to the nonlinear regime. The factors causing changes in the model parameters when applying high-amplitude velocity perturbations are analysed. As a third step, time-domain simulations employing a low-order network model implemented in Simulink® are performed. In this work, the proposed method is applied to a laboratory test rig. The proposed method permits not only the unsteady frequencies of acoustic oscillations to be computed, but the amplitudes of such oscillations as well. Knowing the amplitudes of unstable pressure oscillations, it is possible to determine how these oscillations are harmful to the combustor equipment. The proposed method has a low cost because it does not require any license for computational fluid dynamics software.