Do you understand the following:To be able to diagonalise an nxn matrix, it has to have n linearly independent eigenvectors.For a matrix to be diagonalizable it does not necessarily have to have n different eigenvalues. If v1, v2, v3, ... are linearly independent eigenvectors with corresponding eigenvalues l1, l2, l3, ... , respectively. To make up the matrix D we can add the eigenvalues in any order. However, when we then build the corresponding diagonalizing matrix T we have to use the corresponding eigenvectors in the same order.For a matrix to be diagonalizable is a good thing :)

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BlackTom AI · Accepted Answer

The question presents a concept check about diagonalising an nxn matrix, focusing on eigenvectors, eigenvalues, and the relationship between the order of eigenvalues in D and the order of corresponding eigenvectors in T. 
Option a: 'a. No, I don't get this :(' This choice signals confusion or a lack of understanding of the material. It suggests the responder is not grasping the key point that a matrix can be diagonalised if there are enough linearly independent eigenvectors, even when eigenvalues are not all distinct, and that the ordering between D and T must be matched. This option correctly identifies a misunderstanding rather than a correct interpretation of the concept, and would be incorrect as a demonstration of understanding. 
Option b: 'b. I've got this :)' This choice communicates that the person understands the main idea described: that diagonalisation relies on a full set of linearly independent eigenvectors, that repeated eigenvalues do not preclude diagonalisation if the eigenvectors span the space, and that the eigenvalues can be placed in D in any order so long as the corresponding eigenvectors are arranged in the same order in T. It reflects accurate comprehension of how D and T must be constructed in tandem and how diagonalisation relates to the eigenstructure. 
To expand the reasoning further, consider the core statements: (1) diagonalisation requires n linearly independent eigenvectors, which can happen even with repeated eigenvalues if enough eigenvectors exist; (2) the eigenvalues in D can be permuted arbitrarily, but each permutation must align with the same permutation of eigenvectors in T; (3) the interplay between eigenvectors and eigenvalues is what enables the similarity transformation that yields a diagonal matrix. 
In contrast, the notion implied by option a—that the material is not understood—fails to acknowledge these points: it either ignores the possibility of diagonalising with non-distinct eigenvalues or overlooks the necessity of matching the order between D and T. The reasoning in option b aligns with the established requirements for diagonalisation and demonstrates comprehension of how to apply the concept correctly. 
Overall, option a embodies a lack of understanding, while option b expresses the correct grasp of the diagonalisation process as described in the prompt.

MTH1030 -1035 - S1 2025 MTH1030/35 Week 6 lesson quiz: Eigenvectors and eigenvalues

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