对角化

As advantage of this method, at the same time of diagonalization, one can know the algebraic structure in the Hamiltonian and get the eigenstates that are revealed to be an algebraic coherent state as well as some other possible information of the corresponding physical system.

这种方法的优点是，在用代数法将哈密顿量对角化的同时，不但得出了该系统哈密顿量的代数形式，并且可以得知对应的本征态与代数相干态的关系及对应的物理系统的其他物理信息。

This is quite useful: one may safely enlarge the field ''K'', for instance to get an algebraically closed field; Jordan forms can then be computed over the large field and can be used to determine whether the given matrices are similar over the small field.

不是所有的矩阵都可以对角化，但至少在复数域内，所有的矩阵都相似于一些被称为

The "two-loop diagonalization algorithm" that can overcome the weakness of the pseudo-diagonali-zation algorithm is proposed in this paper.

并针对伪对角化方法存在的不足之处提出一种"双环优势化"方法。

In addition, the representation of differentiation operator in wavelet bases is almost diagonal with a diagonal pre-conditioning operator.

另外微分算子在小波基下的表示具有近似对角线分布而且还存在着一个对角化预正则化算子。

In terns of the general theory of linear algebra, reduced matrix for the operator M are similar to a Jordan matrix J, namely M = S~lJS .

当约化矩阵M不可对角化时，根据线形代数的一般理论，这时约化矩阵M与一个约当矩阵J相似，即M=S~(-1)JS，其中S是关于k，q_0的任意可逆矩阵。

We describe recent developments in the construction of numerical schemes for general (one-dimensional) Hamiltonians: in particular, schemes based on exact diagonalization techniques and on the density matrix renormalization group method.

我们将介绍最新发展的几种处理一维强关联系统的实时演化方法，主要是精确对角化方法和密度矩阵重整化群方法。

B In this paper, we mainly study the condition of reduced matrix for the operator which can not be diagonalized.

然后着重讨论了当约化矩阵M不可对角化时的情形。

The paper simplifies the joint diagonalization of matrices into optimization problem which only includes the eigen matrix. For solving the problem conveniently, each row vector of the eigen matrix is parameterized, then utilizes the improved genetic algorithm to get the optimal parameter.

摘要该文首先将矩阵联合对角化问题化简成一个只含有特征矩阵的优化问题，为了便于求解，文中将待求特征矩阵的每一列向量进行参数化处理，并利用改进的遗传算法寻找最优的新参数。

By using the methods of real representation of complex matrices, companion vector and company vector, we study and solve the problems of Jordan canonical forms, triangular and generalized diagonalization for matrices under consimilarity.

我们通过复矩阵的实表示、友向量和伴向量方法，研究并解决了合相似意义下矩阵的若当标准形、合相似意义下矩阵的三角化和矩阵的广义对角化的问题。

Based on these, parallel computing problem of matrix tensor product is discussed, some parallel computing models are presented, the algorithm complexity is analyzed, and the thought and process are elaborated by an example. block matrix ; tensor product ; permuted similar ; parallel algorithms ; computational complexity

文献〔l论述了Cannon算法在工作站机群上的实现，文献[2]提出了一种基于对角划分的并行算法，文献〔3〕提出了在分布式环境下并行求解对称带状矩阵特征值问题的并行二分/多分法及其改进，文献41给出了稠密对称矩阵三对角化的MPI+OpenMP混合并行算法，还有著名的Cannon

Lugalbanda was a god and shepherd king of Uruk where he was worshipped for over a thousand years.

Lugalbanda 是神和被崇拜了一千年多 Uruk古埃及喜克索王朝国王。

I am coming just now,' and went on perfuming himself with Hunut, then he came and sat.

我来只是现在，'歼灭战perfuming自己与胡努特，那麼，他来到和SAT 。