Real Vector Spaces and the Real Spectral Theorem

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SUMMARY

The discussion centers on the Real Spectral Theorem, which states that in a real inner product space V, an operator T is self-adjoint if and only if V has an orthonormal basis consisting of eigenvectors of T. The proof involves transforming a basis of eigenvectors into an orthonormal basis using a newly defined inner product. The participant expresses confusion about this transformation, specifically regarding the definition of the new scalar product and its implications for the basis vectors.

PREREQUISITES
  • Understanding of real inner product spaces
  • Familiarity with the concept of self-adjoint operators
  • Knowledge of eigenvalues and eigenvectors
  • Ability to manipulate inner products and basis transformations
NEXT STEPS
  • Study the proof of the Real Spectral Theorem in detail
  • Learn how to construct orthonormal bases using Gram-Schmidt process
  • Explore the implications of self-adjoint operators in linear algebra
  • Investigate applications of eigenvalue problems in real inner product spaces
USEFUL FOR

Students of linear algebra, mathematicians focusing on functional analysis, and anyone studying the properties of self-adjoint operators in real inner product spaces.

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Homework Statement


Proof:Suppose that V is a real inner product space and T\in \wp(V). If (v1... vn) is a basis for V consisting of eigenvectors for T, then there exists an inner product for V such that T is self-adjoint.


Homework Equations


The Real Spectral Theorem: Suppose that V is a real-inner product space and T \in \wp(V). Then V has an orthonormal basis consisting of eigenvectors of T if.f. T is self-adjoint.

Eigenvalue / Eigenvector Problem: T(v) = \lambdav


The Attempt at a Solution


Ummm... I have spent days on trying to figure this out, and the only advice my professor gave to me was to use the real spectral theorem. But the only way to do this is by, as my professor goes on, to come up with an inner product that "turns" the basis list into an orthonormal one. But this seems like a complete contradiction... idk ~~~~
 
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I guess your n is the same as the dimension of V? Suppose it is so. Let (v,w)[/tex] be the original scalar product. Then you define new scalar product of two vectors v,w by<br /> <br /> \langle v,w\rangle=\sum_{ij}\delta_{ij} (v,v_i)(w,v_j)<br /> <br /> Your basis is now orthonormal - check it. Then play with it.
 

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