恒星对增长螺旋引力扰动的非线性响应及其对增长模式的致稳作用*

本文计算了在增长的螺旋扰动引力场中恒星响应的非线性效应.结果表明,这一非线性效应会导致Q值的增加,从而降低增长率.对于振幅很小,增长率也较小的螺旋形模式,Q值增加较慢;对于振幅较大或增民率较大的模式,Q值也增加较快,从而有效地抑正振幅的增长.这一调节机制是使得由线性理论所得出的增长模式最终达到准稳状态的原因之一。     

ComBn(m+n≤6)团簇的结构，电子特性和磁性研究

基于密度泛函理论和卡里普索结构预测方法,系统研究了ComBn(m+n≤6)团簇的结构,电子特性和磁性。首先,通过卡里普索结构预测方法获得了体系的基态和亚稳态结构。基于基态结构,利用HOMO-LUMO能隙,垂直电离势,垂直电子亲和势和化学硬度分析了掺杂体系的稳定性。最后,研究了基态结构对应的自然布局分布,自然电子组态等电子特性和磁性。     

剪切形变下掺杂及缺陷对MoS2电子结构的影响

本文利用密度泛函理论,研究剪切形变下掺杂改性及不同类型缺陷对MoS2电子结构的影响。发现：剪切形变下,MoS2+P体系为相对最稳定的结构,掺杂改性相较于缺陷对模型稳定性影响更小;模型MoS2+P+Se中P-Mo键易形成共价键,而其中的Se-Mo键和MoS2+P-Mo-S模型中的P-Mo键,易形成离子键;掺杂使MoS2模型能隙变大,而缺陷使能隙减小,且S和Mo原子共缺陷的模型带隙为0;缺陷相较于掺杂改性模型,更能使Mo原子周围增加电荷聚集度,带隙值更低,更能影响或调控模型的电子结构。     

Uniformity in Computable Structure Theory

We investigate the effects of adding uniformity requirements to concepts in computable structure theory such as computable categoricity (of a structure) and intrinsic computability (of a relation on a computable structure). We consider and compare two different notions of uniformity, previously studied by Kudinov and by Ventsov. We discuss some of their results and establish new ones, while also exploring the connections with the relative computable structure theory of Ash, Knight, Manasse, and Slaman and Chisholm and with previous work of Ash, Knight, and Slaman on uniformity in a general computable structure-theoretical setting.     

The Spectrum of the Two-Dimensional Periodic Schrödinger Operator

The absence of eigenvalues (of infinite multiplicity) for the two-dimensional periodic Schrödinger operator with a variable metric is proved. The method of proof does not use the change of variables reducing the metric to a scalar form.     

Some Conditions for a C0-Semigroup to Be Asymptotically Finite-Dimensional

We study the class of bounded C ₀-semigroups T=(T _t ) _t0 on a Banach space X satisfying the asymptotic finite dimensionality condition: codim X ₀(T)<, where X ₀(T):={x X:lim_t T _t x=0}. We prove a theorem which provides some necessary and sufficient conditions for asymptotic finite dimensionality.     

Convergence Dynamics of Delayed Hopfield-Type Neural Networks Under Almost Periodic Stimuli

Convergence dynamics of Hopfield-type neural networks subjected to almost periodic external stimuli are investigated. In this article, we assume that the network parameters vary almost periodically with time and we incorporate variable delays in the processing part of the network architectures. By employing Halanay inequalities, we obtain delay independent sufficient conditions for the networks to converge exponentially toward encoded patterns associated with the external stimuli. The networks are guaranteed to have exponentially hetero-associative stable encoding of the external stimuli.     

Stability of Markovian structure observed in high frequency foreign exchange data

Contrary to the common sense in economics and financial engineering, price fluctuations at very fine level of motion exhibit various evidences against the efficient market hypothesis. We attempt to investigate this issue by studying extensive amount of foreign currency exchange data for over five years at the finest level of resolution. We specifically focus on the proposed stability in binomial conditional probabilities originally found in much smaller examples of financial time series. In order to handle very large data, we have written an efficient program in C that automatically generates those conditional probabilities. It is found that the stability is maintained for extremely large time duration that covers almost the entire period. Based on the length of conditions for which the conditional probabilities are distinguishable each other, we identify the length of memory being less than 3 movements.     

Permutation graphs, fast forward permutations, and sampling the cycle structure of a permutation

PS_N is a fast forward permutation if for each m the computational complexity of evaluating P^m(x) is small independently of m and x. Naor and Reingold constructed fast forward pseudorandom cycluses and involutions. By studying the evolution of permutation graphs, we prove that the number of queries needed to distinguish a random cyclus from a random permutation in S_N is Θ(N) if one does not use queries of the form P^m(x), but is only Θ(1) if one is allowed to make such queries. We construct fast forward permutations which are indistinguishable from random permutations even when queries of the form P^m(x) are allowed. This is done by introducing an efficient method to sample the cycle structure of a random permutation, which in turn solves an open problem of Naor and Reingold.     

Sequential Estimation of the Parameters in a Trigonometric Regression Model with the Gaussian Coloured Noise

This paper considers the estimation problem for a trigonometric regression model with the noise specified by the Ornstein–Uhlenbeck process with unknown parameter. We propose a sequential procedure which ensures a prescribed mean square precision uniformly in the nuisance parameter. The asymptotic behaviour of the procedure duration mean has been studied. This revised version was published online in August 2006 with corrections to the Cover Date.