Math Problem Statement

Find all distinct (real or complex) eigenvalues of A. Then find a basis for the eigenspace of A corresponding to each eigenvalue. For each eigenvalue, specify the dimension of the eigenspace corresponding to that eigenvalue, then enter the eigenvalue followed by the basis of the eigenspace corresponding to that eigenvalue. A = [[-1, 4, -6], [0, 6, -2], [0, 5, 0]].

Solution

To solve the problem, we will calculate the eigenvalues and eigenvectors for the given matrix AA. Let me walk you through the steps:

Step 1: Find the Eigenvalues

The eigenvalues are found by solving the characteristic equation: det(AλI)=0\det(A - \lambda I) = 0 where λ\lambda represents the eigenvalues.

The matrix AA is:

-1 & 4 & -6 \\ 0 & 6 & -2 \\ 0 & 5 & 0 \end{bmatrix}$$ The characteristic matrix $$A - \lambda I$$ is: $$A - \lambda I = \begin{bmatrix} -1 - \lambda & 4 & -6 \\ 0 & 6 - \lambda & -2 \\ 0 & 5 & -\lambda \end{bmatrix}$$ We then compute the determinant: \[ \det(A - \lambda I) = \det\begin{bmatrix} -1 - \lambda & 4 & -6 \\ 0 & 6 - \lambda & -2 \\ 0 & 5 & -\lambda \end{bpy as sp # Define the matrix and variable for eigenvalues λ = sp.symbols('λ') A = sp.Matrix([ [-1 - λ, 4, -6], [0, 6 - λ, -2], [0, 5, -λ] ]) # Calculate the determinant of (A - λI) char_eq = A.det() # Solve the characteristic equation for eigenvalues eigenvalues = sp.solve(char_eq, λ) char_eqThe characteristic equation is: $$-\lambda^3 + 5\lambda^2 - 4\lambda - 10 = 0$$ The eigenvalues are: 1. $$\lambda = -1$$ 2. $$\lambda = 3 - i$$ (complex eigenvalue) 3. $$\lambda = 3 + i$$ (complex eigenvalue) ### Step 2: Find the Basis for Each Eigenspace For each eigenvalue, we solve $$(A - \lambda I)\mathbf{v} = 0$$ to find the eigenvectors (basis of the eigenspace). I will A_original = sp.Matrix([ [-1, 4, -6], [0, 6, -2], [0, 5, 0] ]) # Find eigenvectors for each eigenvalue eigenvectors = {} for eigenvalue in eigenvalues: eigenspace_matrix = A_original - eigenvalue * sp.eye(3) eigenspace = eigenspace_matrix.nullspace() eigenvectors[eigenvalue] = eigenspace eThe eigenvectors (basis for the eigenspaces) corresponding to each eigenvalue are: 1. For $$\lambda = -1$$: - Basis: $$\begin{bmatrix} 1 \\ 0 \\ 0 \end{bmatrix}$$ - Dimension of eigenspace: 1 2. For $$\lambda = 3 - i$$ (complex eigenvalue): - Basis: $$\begin{bmatrix} -\frac{4}{5} - \frac{2i}{5} \\ \frac{3}{5} - \frac{i}{5} \\ 1 \end{bmatrix}$$ - Dimension of eigenspace: 1 3. For $$\lambda = 3 + i$$ (complex eigenvalue): - Basis: $$\begin{bmatrix} -\frac{4}{5} + \frac{2i}{5} \\ \frac{3}{5} + \frac{i}{5} \\ 1 \end{bmatrix}$$ - Dimension of eigenspace: 1 ### Summary - Each eigenvalue has an eigenspace dimension of 1. - The real eigenvalue has a real basis vector, while the complex eigenvalues have complex basis vectors. Would you like a step-by-step explanation or further clarifications? Here are 5 related questions for further exploration: 1. How are eigenvalues used in diagonalizing a matrix? 2. What are the properties of the eigenspaces of a matrix with complex eigenvalues? 3. Can you visualize the relationship between eigenvalues and eigenvectors? 4. How does the determinant relate to the eigenvalues of a matrix? 5. What are the physical interpretations of eigenvalues and eigenvectors in real-world problems? **Tip:** Understanding the role of eigenvalues and eigenvectors can

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Math Problem Analysis

Mathematical Concepts

Linear Algebra
Eigenvalues
Eigenvectors
Eigenspace

Formulas

Characteristic equation: det(A - λI) = 0
Matrix determinant
Null space computation for eigenvectors

Theorems

Eigenvalue-Eigenvector Theorem
Fundamental Theorem of Algebra (complex eigenvalues)

Suitable Grade Level

Undergraduate