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Kinji Kimura

Publications and source records attributed to Kinji Kimura.

4 recordsLinked to original sources

A Lax pair of the discrete Euler top in terms of quaternions

We proposed the discrete Euler top in 2000. In that paper, exact solutions and conserved quantities are described. However, a Lax pair of our proposed discrete Euler top is not contained. Moreover, the Lax pair is still unknown. In this paper, from a generalized eigenvalue problem, we obtain the Lax pair of the discrete Euler top. In addition, we introduce another Lax pair of the discrete Euler top in terms of quaternions.

nlin.SI

A new subtraction-free formula for lower bounds of the minimal singular value of an upper bidiagonal matrix

Traces of inverse powers of a positive definite symmetric tridiagonal matrix give lower bounds of the minimal singular value of an upper bidiagonal matrix. In a preceding work, a formula for the traces which gives the diagonal entries of the inverse powers is presented. In this paper, we present another formula which gives the traces based on a quite different idea from the one in the preceding work. An efficient implementation of the formula for practice is also presented.

math.NA

On Implementation and Evaluation of Inverse Iteration Algorithm with compact WY Orthogonalization

A new inverse iteration algorithm that can be used to compute all the eigenvectors of a real symmetric tri-diagonal matrix on parallel computers is developed. The modified Gram-Schmidt orthogonalization is used in the classical inverse iteration. This algorithm is sequential and causes a bottleneck in parallel computing. In this paper, the use of the compact WY representation is proposed in the orthogonalization process of the inverse iteration with the Householder transformation. This change results in drastically reduced synchronization cost in parallel computing. The new algorithm is evaluated on both an 8-core and a 32-core parallel computer, and it is shown that the new algorithm is greatly faster than the classical inverse iteration algorithm in computing all the eigenvectors of matrices with several thousand dimensions.

math.NA