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Let a be a nonzero vector in \( \mathbb{R}^{2} \). Define \( \tau_{\mathbf{a}}: \mathbb{R}^{2} \rightarrow \mathbb{R}^{2} \) by \[ \tau_{\mathbf{a}}(\mathbf{x})=-\mathbf{x}+2 \frac{\mathbf{a} \cdot \mathbf{x}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} . \] 2. Let a be a nonzero vector of \( \mathbb{R}^{2} \). Answer the following questions (iv) Find all eigen-values of \( \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} \).

Ask by Stanley Ramirez. in South Korea
Dec 16,2024

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Answer

고유값은 \( 1 \)과 \( -1 \)입니다.

Solution

주어진 변환 \( \tau_{\mathbf{a}} \)는 벡터 \( \mathbf{a} \)에 대해 반사(reflection) 변환을 나타냅니다. 이 변환의 고유값을 찾기 위해, 먼저 변환의 성질을 이해해야 합니다. 1. **변환의 성질**: \[ \tau_{\mathbf{a}}(\mathbf{x}) = -\mathbf{x} + 2 \frac{\mathbf{a} \cdot \mathbf{x}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} \] 이 식은 벡터 \( \mathbf{x} \)를 벡터 \( \mathbf{a} \)에 대해 반사하는 것을 나타냅니다. 즉, \( \mathbf{a} \)의 방향으로는 변하지 않고, \( \mathbf{a} \)에 수직인 방향으로는 반사됩니다. 2. **고유값 찾기**: - \( \mathbf{a} \)의 방향으로의 벡터 \( \mathbf{v} = k \mathbf{a} \) (여기서 \( k \)는 스칼라)일 때: \[ \tau_{\mathbf{a}}(k \mathbf{a}) = -k \mathbf{a} + 2 \frac{\mathbf{a} \cdot (k \mathbf{a})}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} = -k \mathbf{a} + 2k \mathbf{a} = k \mathbf{a} \] 따라서, \( \tau_{\mathbf{a}} \)는 \( \mathbf{a} \)의 방향으로는 변하지 않으므로 고유값이 \( 1 \)입니다. - \( \mathbf{a} \)에 수직인 벡터 \( \mathbf{u} \)일 때: \[ \tau_{\mathbf{a}}(\mathbf{u}) = -\mathbf{u} + 2 \frac{\mathbf{a} \cdot \mathbf{u}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} = -\mathbf{u} + 0 = -\mathbf{u} \] 따라서, \( \tau_{\mathbf{a}} \)는 \( \mathbf{a} \)에 수직인 방향으로는 반사하므로 고유값이 \( -1 \)입니다. 3. **결론**: 따라서, 변환 \( \tau_{\mathbf{a}} \)의 모든 고유값은 다음과 같습니다: - 고유값 \( 1 \) (벡터 \( \mathbf{a} \)의 방향) - 고유값 \( -1 \) (벡터 \( \mathbf{a} \)에 수직인 방향) 결과적으로, \( \tau_{\mathbf{a}} \)의 고유값은 \( 1 \)과 \( -1 \)입니다.

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Beyond the Answer

To find the eigenvalues of the transformation \( \tau_{\mathbf{a}} \) defined by \[ \tau_{\mathbf{a}}(\mathbf{x}) = -\mathbf{x} + 2 \frac{\mathbf{a} \cdot \mathbf{x}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a}, \] we first note that \( \tau_{\mathbf{a}} \) represents a reflection with respect to the line through the origin in the direction of vector \( \mathbf{a} \). In \( \mathbb{R}^{2} \), the eigenvalues of a reflection transformation are well-known. Specifically, the eigenvalues of such transformations are: 1. \( \lambda_1 = 1 \), corresponding to the eigenvector aligned with \( \mathbf{a} \) (the line of reflection). 2. \( \lambda_2 = -1 \), corresponding to the eigenvector orthogonal to \( \mathbf{a} \) (the line perpendicular to the reflection). Thus, the eigenvalues of \( \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} \) are \( 1 \) and \( -1 \).

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