Discussion Overview
The discussion revolves around finding a symmetric matrix A from given orthogonal eigenvectors represented in matrix H. Participants explore the relationship between eigenvectors, eigenvalues, and the construction of matrix A, addressing both theoretical and practical aspects of the problem.
Discussion Character
- Exploratory
- Technical explanation
- Mathematical reasoning
- Debate/contested
Main Points Raised
- Michael inquires about deriving matrix A from the orthogonal eigenvectors in matrix H.
- One participant suggests writing the eigenvectors as columns of matrix A and analyzing the transformation of a specific vector.
- Another participant questions the notation and the choice of the vector [1,0].
- A participant assumes that matrix A should be symmetric due to the orthogonality of the eigenvectors.
- There is a discussion about the lack of fixed eigenvalues, leading to an infinite number of matrices with the same eigenvectors but different eigenvalues.
- One participant proposes using the relationship between the eigenvalues and the eigenvectors to derive equations for the parameters of matrix A.
- A later reply details the process of obtaining equations for the eigenvalues based on the structure of matrix A and the eigenvectors.
- Another participant claims to have solved the problem, providing a specific form for matrix A and a relationship for parameter b in terms of a and d.
- The solution includes a validation step using statistical programming in R to confirm the results.
Areas of Agreement / Disagreement
Participants express differing views on the necessity of fixed eigenvalues, with some arguing that without them, the matrix cannot be uniquely determined. The discussion remains unresolved regarding the implications of not having fixed eigenvalues.
Contextual Notes
Participants note that the absence of fixed eigenvalues introduces significant freedom in determining matrix A, leading to multiple valid matrices that share the same eigenvectors.