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The q-Toda equation is derived from replacing ordinary derivatives with q-derivatives in the famous Toda equation. In this paper, we associate an extension of the q-Toda equation with matrix eigenvalue problems, and then show applications of its time-discretization to computing matrix eigenvalues. With respect to the Lotka–Volterra system, we also have the similar discussion on the case of the Toda equation. [ABSTRACT FROM AUTHOR]

In this paper, we derive a new similarity transformation from the discrete Lotka-Volterra system by taking an infinite limit of the discretization parameter. The proposed similarity transformation is shown to be applicable for computing singular values of a bidiagonal matrix. The forward stability of it is also verified in floating point arithmetic. [ABSTRACT FROM AUTHOR]

The integrable discrete hungry Lotka–Volterra (dhLV) system is easily transformed to the qd-type dhLV system, which resembles the recursion formula of the qd algorithm for computing matrix eigenvalues. Some of the qd-type dhLV variables play a role for assisting the time evolution of the others. This property does not appear in the original dhLV system. In this article, we first show the existence of a centre manifold for the qd-type dhLV system. With the help of the centre manifold theory, we next investigate the local convergence of the qd-type dhLV system, and then clarify the monotonicity related to the qd-type dhLV variables at the final phase of the convergence. [ABSTRACT FROM PUBLISHER]

The cyclic reduction method is a direct method for solving tridiagonal linear systems. At the first step of this method, a tridiagonal coefficient matrix is transformed into a pentadiagonal form. In this article, we prove that the condition number for eigenvalues of some classes of coefficient matrices always decreases after the first step of the cyclic reduction method. [ABSTRACT FROM AUTHOR]

Solvers for linear systems with tridiagonal coefficient matrices sometimes employ direct methods such as the Gauss elimination method or the cyclic reduction method. In each step of the cyclic reduction method, nonzero offdiagonal entries in the coefficient matrix move incrementally away from diagonal entries and eventually vanish. The steps of the cyclic reduction method are generalized as forms of the stride reduction method. For example, the 2-stride reduction method coincides with the 1st step of the cyclic reduction method which transforms tridiagonal linear systems into pentadiagonal systems. In this paper, we explain arbitrary-stride reduction for linear systems with coefficient matrices with three nonzero bands. We then show that arbitrary-stride reduction is equivalent to a combination of 2-stride reduction and row and column permutations. We thus clarify eigenvalue clustering of coefficient matrices in the step-by-step process of the stride reduction method. We also provide two examples verifying this property. [ABSTRACT FROM AUTHOR]