Math Problem Statement
The image you've provided shows a matrix A A and the corresponding eigenvalues and eigenvectors.
Given:
A
( 3 10 5 − 2 − 3 − 4 3 5 7 ) A=
3 −2 3
10 −3 5
5 −4 7
Solution
You provided a 3x3 matrix , which is:
3 & 10 & 5 \\ -2 & -3 & -4 \\ 3 & 5 & 7 \end{pmatrix}$$ To find the **eigenvalues** and **eigenvectors** of matrix $$A$$, we follow these steps: 1. **Find the Eigenvalues**: - Solve the characteristic equation: $$\det(A - \lambda I) = 0$$, where $$\lambda$$ is the eigenvalue and $$I$$ is the identity matrix. 2. **Find the Eigenvectors**: - Once the eigenvalues $$\lambda$$ are found, substitute each into $$(A - \lambda I)v = 0$$, where $$v$$ is the corresponding eigenvector. Solve this system of equations for $$v$$. Let me compute the eigenvalues and eigenvectors for matrix $$A$$.The eigenvalues and eigenvectors of the matrix $$A$$ are: ### Eigenvalues: $$\lambda_1 = 3, \quad \lambda_2 = 2 + 5.78 \times 10^{-8}i, \quad \lambda_3 = 2 - 5.78 \times 10^{-8}i$$ The second and third eigenvalues are very close to $$2$$, indicating that they are essentially real with minimal imaginary components. ### Eigenvectors: Corresponding to the eigenvalues, the normalized eigenvectors are: For $$\lambda_1 = 3$$: $$v_1 = \begin{pmatrix} -0.4082 \\ -0.4082 \\ 0.8165 \end{pmatrix}$$ For $$\lambda_2 \approx 2$$: $$v_2 = \begin{pmatrix} -0.6804 \\ -0.2722 \\ 0.6804 \end{pmatrix}$$ For $$\lambda_3 \approx 2$$: $$v_3 = \begin{pmatrix} -0.6804 \\ -0.2722 \\ 0.6804 \end{pmatrix}$$ Let me know if you want further details or explanations! Here are some related questions: 1. How are eigenvalues used in solving systems of linear equations? 2. What is the significance of the geometric multiplicity of an eigenvalue? 3. How can you interpret the physical meaning of eigenvectors in real-world applications? 4. How are eigenvalues and eigenvectors used in diagonalizing a matrix? 5. What conditions must a matrix satisfy for all its eigenvalues to be real? **Tip:** Small imaginary components in eigenvalues often arise due to numerical rounding errors; they can usually be treated as real values.Ask a new question for Free
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Math Problem Analysis
Mathematical Concepts
Linear Algebra
Eigenvalues
Eigenvectors
Matrix Theory
Formulas
Eigenvalue equation: det(A - λI) = 0
Eigenvector equation: (A - λI)v = 0
Theorems
Eigenvalue theorem: Solutions to det(A - λI) = 0 yield the eigenvalues
Eigenvector theorem: Eigenvectors correspond to non-zero solutions of (A - λI)v = 0
Suitable Grade Level
University level (Linear Algebra)
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