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Hermitian Matrix

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Hermitian matrix [er′mish·ən ′mā·triks]
(mathematics)
A matrix which equals its conjugate transpose matrix, that is, is self-adjoint.

Hermitian Matrix 

(or self-adjoint matrix), a matrix coincident with its adjoint, that is, a matrix such that aik= āki, where ā is the complex conjugate of the number a. If the elements of a Hermitian matrix are real, then the matrix is symmetric. A Hermitian matrix has real eigenvalues λ1, λ2, …, λn and corresponds to a linear transformation in a complex n-dimensional space that reduces to stretchings by ǀλiǀ in n mutually perpendicular directions and reflections in the planes orthogonal to the directions for which λi < 0. A bilinear form

whose coefficients form a Hermitian matrix, is called a Hermitian form. Any matrix can be written in the form A1 + iA2, where A1 and A2 are Hermitian matrices, and in the form A ∪, where A is a Hermitian matrix and U is a unitary matrix. If A and B are Hermitian matrices, then A B is a Hermitian matrix if and only if A and B commute.



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The analysis is general for any linear operator D which could be modeled with a Hermitian matrix and is not limited to sampling problems.
1 Solving the Hamiltonian Equation Sequentially and in Parallel for a Single Nanoparticle Given that only nearest neighbor coupling is included in our models, the matrix we work with is a large, sparse, banded Hermitian matrix.
If A is an n x n Hermitian matrix, then it is well known that all the eigenvalues of A are real.
 
 
 
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