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2005•arXiv (Cornell University)Open access

Generation of Matrices with Specified Eigenvalues and their Diagonalization

Habatwa Vincent Mweene

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Abstract

We present a prescription for forming matrices with specified eigenvalues and known eigenvectors. With this method, we can form Hermitian, anti-Hermitian, symmetric and general matrices with arbitrary eigenvalues. In addition we propose an algorithm for diagonalizing such matrices. The functions required for the realization of this are probability amplitudes connecting observables with discrete eigenvalue spectra and can be obtained from spin theory. For the example case of $5\times 5$ matrices, these functions are given.

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We present a prescription for forming matrices with specified eigenvalues and known eigenvectors. With this method, we can form Hermitian, anti-Hermitian, symmetric and general matrices with arbitrary eigenvalues. In addition we propose an algorithm for diagonalizing such matrices. The functions required for the realization of this are probability amplitudes connecting observables with discrete eigenvalue spectra and can be obtained from spin theory. For the example case of $5\times 5$ matrices, these functions are given.

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Available abstract

We present a prescription for forming matrices with specified eigenvalues and known eigenvectors. With this method, we can form Hermitian, anti-Hermitian, symmetric and general matrices with arbitrary eigenvalues. In addition we propose an algorithm for diagonalizing such matrices. The functions required for the realization of this are probability amplitudes connecting observables with discrete eigenvalue spectra and can be obtained from spin theory. For the example case of $5\times 5$ matrices, these functions are given.

Key concepts: Hermitian matrix, Eigenvalues and eigenvectors, Realization (probability), Mathematics, Pure mathematics, Matrix (chemical analysis), Observable, Spectrum of a matrix

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