Explicit formulas for Hecke Gauss sums in quadratic number fields

We derive an explicit formula for Hecke Gauss sums of quadratic number fields. As an immediate consequence we obtain a quadratic reciprocity law in quadratic number fields which generalizes the classical one given by Hecke. The proofs use, apart from the well-known formulas for ordinary Gauss sums, only elementary algebraic manipulations.     

An analytic center quadratic cut method for the convex quadratic feasibility problem

 We consider a quadratic cut method based on analytic centers for two cases of convex quadratic feasibility problems. In the first case, the convex set is defined by a finite yet large number, N, of convex quadratic inequalities. We extend quadratic cut algorithm of Luo and Sun [3] for solving such problems by placing or translating the quadratic cuts directly through the current approximate center. We show that, in terms of total number of addition and translation of cuts, our algorithm has the same polynomial worst case complexity as theirs [3]. However, the total number of steps, where steps consist of (damped) Newton steps, function evaluations and arithmetic operations, required to update from one approximate center to another is , where ε is the radius of the largest ball contained in the feasible set. In the second case, the convex set is defined by an infinite number of certain strongly convex quadratic inequalities. We adapt the same quadratic cut method for the first case to the second one. We show that in this case the quadratic cut algorithm is a fully polynomial approximation scheme. Furthermore, we show that, at each iteration, k, the total number steps (as described above) required to update from one approximate center to another is at most , with ε as defined above. Received: April 2000 / Accepted: June 2002 Published online: September 5, 2002 Key words. convex quadratic feasibility problem – interior-point methods – analytic center – quadratic cuts – potential function     

Runge-Kutta methods for quadratic ordinary differential equations

Many systems of ordinary differential equations are quadratic: the derivative can be expressed as a quadratic function of the dependent variable. We demonstrate that this feature can be exploited in the numerical solution by Runge-Kutta methods, since the quadratic structure serves to decrease the number of order conditions. We discuss issues related to construction design and implementation and present a number of new methods of Runge-Kutta and Runge-Kutta-Nyström type that display superior behaviour when applied to quadratic ordinary differential equations.     

实二次域的一个同余式

本文证明了关于实二次域的类数和某类特征和的同余式,同时给出某类实二次域的类数可除性的一个判别法则．     

Smooth lattices over quadratic integers

We construct lattices with quadratic structure over the integers in quadratic number fields having the property that the rank of the quadratic structure is constant and equal to the rank of the lattice in all reductions modulo maximal ideals. We characterize the case in which such lattices are free. The construction gives a representative of the genus of such lattices as an orthogonal sum of “standard” pieces of ranks 1–4 and covers the case of the discriminant of the real quadratic number field congruent to 1 modulo 8 for which a general construction was not known.      

Diskriminanten und Picard-Invarianten freier quadratischer Erweiterungen

For commutative rings R, in which 2 is not a zero divisor, we give seven-term exact sequences, whose middle terms are the discriminant map or the Picard invariant of free quadratic extensions of R. As an application of our results we determine for all orders in quadratic number fields the group of free quadratic extensions and the group of quadratic extensions with normal basis.     

Reduction of indefinite quadratic programs to bilinear programs

Indefinite quadratic programs with quadratic constraints can be reduced to bilinear programs with bilinear constraints by duplication of variables. Such reductions are studied in which: (i) the number of additional variables is minimum or (ii) the number of complicating variables, i.e., variables to be fixed in order to obtain a linear program, in the resulting bilinear program is minimum. These two problems are shown to be equivalent to a maximum bipartite subgraph and a maximum stable set problem respectively in a graph associated with the quadratic program. Non-polynomial but practically efficient algorithms for both reductions are thus obtaine.d Reduction of more general global optimization problems than quadratic programs to bilinear programs is also briefly discussed.     

On the average speed of Lemke's algorithm for quadratic programming

In this paper, we show that the average number of steps of the Lemke algorithm for the quadratic programming problems grows at most linearly in the number of variables while fixing the number of constraints. The result and method were motivated by Smale's result on linear programming problems [cf. 4]. We also give the probability that a quadratic programming problem indeed possesses a finite optimal solution.     

Computation of class numbers of quadratic number fields

We explain how one can dispense with the numerical computation of approximations to the transcendental integral functions involved when computing class numbers of quadratic number fields. We therefore end up with a simpler and faster method for computing class numbers of quadratic number fields. We also explain how to end up with a simpler and faster method for computing relative class numbers of imaginary abelian number fields.

     

A GENERALIZATION OF FINSLER'S THEOREM FOR QUADRATIC INEQUALITIES AND EQUALITIES

ABSTRACT

A generalization is given of Finsler's theorem on the positivity of a quadratic form subject to a quadratic equality. The generalized result is, under a certain assumption, a set of necessary and sufficient conditions for non-negativity of a quadratic form subject to an arbitrary number of quadratic inequality and equality constraints. Certain properties of matrix inverses are deduced using the conditions.     

An estimate for the number of consecutive quadratic residues

The problem of estimation of the maximal number H of consecutive integer numbers such that they all are either quadratic residues or quadratic nonresidues modulo a prime number p is considered.     

有限域上二次型序列与几何序列的互相关性

§1Introduction Letpbeaprimenumber,q=pm,andFqdenotethefinitefieldwithqelements.Fo anyn≥1,Trmnm(·)isthetracefunctionfromFqntoFq.LetαbeaprimitiveelementofFq and{α1,α2,...,αn}beabasisofFqnoverFq.Definition1.ForanonlinearfunctionffromFqtoFp,thesequenceS={Si}qn-1i=1withit termdefinedby Si=f(Trmnm(αi))(1iscalledageometricsequence.SuchageometricsequenceShasperioddividingqn-1.Geometricsequences includingm-sequence[1],GMWsequence[2,3],cascadedGMWsequence[4,5]andman others[6],mayhavelar…     

A New Quadratic Semi-infinite Programming Algorithm Based on Dual Parametrization

The so called dual parameterization method for quadratic semi-infinite programming (SIP) problems is developed recently. A dual parameterization algorithm is also proposed for numerical solution of such problems. In this paper, we present and improved adaptive algorithm for quadratic SIP problems with positive definite objective and multiple linear infinite constraints. In each iteration of the new algorithm, only a quadratic programming problem with a limited dimension and a limited number of constraints is required to be solved. Furthermore, convergence result is given. The efficiency of the new algorithm is shown by solving a number of numerical examples.     

Minimal representation of quadratically constrained convex feasible regions

In this paper we are concerned with characterizing minimal representations of feasible regions defined by both linear and convex quadratic constraints. We say that representation is minimal if every other representation has either more quadratic constraints, or has the same number of quadratic constraints and at least as many linear constraints. We will prove that a representation is minimal if and only if it contains no redundant constraints, no pseudo-quadratic constraints and no implicit equality constraints. We define a pseudo-quadratic constraint as a quadratic constraint that can be replaced by a finite number of linear constraints. In order to prove the minimal representation theorem, we also prove that if the surfaces of two quadratic constraints match on a ball, then they match everywhere.In this paper we also provide algorithms that can be used to detect implicit equalities and pseudoquadratic constraints. The redundant constraints can be identified using the hypersphere directions (HD) method.Corresponding author.     

On the cyclicity of a 2-polycycle for quadratic systems

It has been already known that the maximum number of limit cycles near a homoclinic loop of a quadratic Hamiltonian system under quadratic perturbations is two. However, the problem of finding the maximum number of limit cycles in the 2-polycycle case is still open. This paper addresses the problem in some detail and solves it partially.     

Subsequent Convergence of Iterative Methods with Applications to Real-Time Model-Predictive Control

In performing online model-predictive control of dynamical systems, it is necessary to solve a sequence of optimization problems (typically quadratic programs) in real time so as to generate the best trajectory. Since only a low fixed number of iterations can be executed in real time, it is not possible to solve each quadratic program to optimality. However, numerical experiments show that, if we use information from the numerical solution of the previous quadratic program to construct a warm start for the current quadratic program, there is a time step after which the usual stopping criteria will be satisfied within the fixed number of iterations for all subsequent optimization problems. This phenomenon is called subsequent convergence and will be analyzed for families of nonlinear equations. Computational results are presented to illustrate the theory and associated computational artifacts.     

Approximating Global Quadratic Optimization with Convex Quadratic Constraints

We consider the problem of approximating the global maximum of a quadratic program (QP) subject to convex non-homogeneous quadratic constraints. We prove an approximation quality bound that is related to a condition number of the convex feasible set; and it is the currently best for approximating certain problems, such as quadratic optimization over the assignment polytope, according to the best of our knowledge.     

Modular Properties of Theta-Functions and Representation of Numbers by Positive Quadratic Forms

By means of the theory of modular forms the formulas for a number of representations of positive integers by two positive quaternary quadratic forms of steps 36 and 60 and by all positive diagonal quadratic forms with seven variables of step 8 are obtain.     

一类不连续平面二次微分系统的极限环

本文考虑了一类不连续平面二次可积非Hamilton微分系统在二次扰动下的极限环个数问题.利用一阶平均法,我们得到了从该系统中心的周期环域至少可以分支出5个极限环的结论.该结果表明不连续二次微分系统比其相应光滑微分系统至少可以多分支出2个极限环.