Hermitian Operators and Projectors in Linear Algebra

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SUMMARY

The discussion centers on the properties of Hermitian operators and projectors in linear algebra, specifically examining two matrices: one that is not Hermitian and another that is Hermitian and serves as a projector. The first matrix, represented as [[1, 1], [0, 0]], has eigenvalues λ1=1 and λ2=0, while the second matrix, [[1, 0], [0, 0]], is Hermitian and idempotent. The conversation highlights the importance of basis transformations in determining the symmetry of operators and clarifies the definition of projectors as linear transformations with orthogonal null space and range.

PREREQUISITES
  • Understanding of linear transformations
  • Familiarity with eigenvalues and eigenvectors
  • Knowledge of Hermitian matrices and their properties
  • Concept of projectors in inner product spaces
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  • Study the properties of Hermitian matrices in detail
  • Learn about basis transformations and their effects on matrix representations
  • Explore the concept of idempotent matrices and their applications
  • Investigate the distinctions between projectors in different mathematical contexts
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Students and professionals in mathematics, particularly those specializing in linear algebra, quantum mechanics, or any field requiring a deep understanding of matrix theory and operator properties.

LagrangeEuler
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Matrix
<br /> \left[<br /> \begin{array}{rr}<br /> 1 &amp; 1 \\<br /> 0&amp; 0 \\<br /> \end{array} \right]
is not symmetric. When we find eigenvalues of that matrix we get ##\lambda_1=1##, ##\lambda_2=0##, or we get matrix
<br /> \left[<br /> \begin{array}{rr}<br /> 1 &amp; 0 \\<br /> 0&amp; 0 \\<br /> \end{array} \right].
First matrix is not hermitian, whereas second one it is. How it is possible that some operator is hermitian in one basis, and is not in the other one. Second matrix is also a projector, and the first one it is not. How that is possible.
 
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Have you considered how a basis transformation has to look like, in order to conserve symmetry? Does yours look like one? And what do you mean by a projector? The first matrix is also a projection, i.e. surjective, just not at the same angle.
 
fresh_42 said:
And what do you mean by a projector?.

In English linear algebra references, a projector (on an inner product space) typically is a linear transformation that is a projection, and that has orthogonal null space and range, i.e., idempotent and Hermitian. I am not sure if other languages make this distinction.
 
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