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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. (iii) Find the matrix \( \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} \) of \( \tau_{\mathbf{a}} \) with respect to \( \mathcal{B} \) and \( \mathcal{B} \).

Ask by Smith Wheeler. in South Korea
Dec 16,2024

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Answer

변환 \( \tau_{\mathbf{a}} \)의 행렬 \( \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} \)는 다음과 같습니다: \[ \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} = \begin{pmatrix} 1 - 2\frac{a_1^2}{a_1^2 + a_2^2} & -2\frac{a_1 a_2}{a_1^2 + a_2^2} \\ -2\frac{a_1 a_2}{a_1^2 + a_2^2} & 1 - 2\frac{a_2^2}{a_1^2 + a_2^2} \end{pmatrix} \] 여기서 \( a_1 \)과 \( a_2 \)는 벡터 \( \mathbf{a} \)의 성분입니다.

Solution

주어진 변환 \( \tau_{\mathbf{a}} \)는 다음과 같이 정의됩니다: \[ \tau_{\mathbf{a}}(\mathbf{x}) = -\mathbf{x} + 2 \frac{\mathbf{a} \cdot \mathbf{x}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} \] 여기서 \( \mathbf{a} \)는 \( \mathbb{R}^2 \)의 비영벡터입니다. 이 변환은 벡터 \( \mathbf{a} \)에 대한 반사(reflection) 변환입니다. 변환의 행렬을 구하기 위해, 먼저 \( \mathcal{B} \)를 기저로 설정해야 합니다. 일반적으로 \( \mathcal{B} = \{\mathbf{e_1}, \mathbf{e_2}\} \)와 같은 표준 기저를 사용할 수 있습니다. 여기서 \( \mathbf{e_1} = \begin{pmatrix} 1 \\ 0 \end{pmatrix} \)와 \( \mathbf{e_2} = \begin{pmatrix} 0 \\ 1 \end{pmatrix} \)입니다. 1. **기저 벡터에 대한 변환 계산**: - \( \tau_{\mathbf{a}}(\mathbf{e_1}) \)와 \( \tau_{\mathbf{a}}(\mathbf{e_2}) \)를 계산합니다. \[ \tau_{\mathbf{a}}(\mathbf{e_1}) = -\mathbf{e_1} + 2 \frac{\mathbf{a} \cdot \mathbf{e_1}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} \] \[ \tau_{\mathbf{a}}(\mathbf{e_2}) = -\mathbf{e_2} + 2 \frac{\mathbf{a} \cdot \mathbf{e_2}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} \] 2. **행렬 표현**: - \( \tau_{\mathbf{a}}(\mathbf{e_1}) \)와 \( \tau_{\mathbf{a}}(\mathbf{e_2}) \)를 각각 \( \mathcal{B} \)의 기저 벡터로 표현합니다. - 이 두 벡터를 열벡터로 하여 행렬을 구성합니다. 3. **결과**: - 최종적으로, 변환 \( \tau_{\mathbf{a}} \)의 행렬 \( \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} \)는 다음과 같은 형태가 됩니다: \[ \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} = \begin{pmatrix} 1 - 2\frac{a_1^2}{a_1^2 + a_2^2} & -2\frac{a_1 a_2}{a_1^2 + a_2^2} \\ -2\frac{a_1 a_2}{a_1^2 + a_2^2} & 1 - 2\frac{a_2^2}{a_1^2 + a_2^2} \end{pmatrix} \] 여기서 \( a_1 \)과 \( a_2 \)는 벡터 \( \mathbf{a} = \begin{pmatrix} a_1 \\ a_2 \end{pmatrix} \)의 성분입니다.

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To find the matrix \( \left[\tau_{\mathbf{a}}\right]_{\mathcal{B}}^{\mathcal{B}} \) for the transformation \( \tau_{\mathbf{a}} \), we proceed with the following steps: ### Step 1: Define the Vector \( \mathbf{a} \) and the Basis \( \mathcal{B} \) Let \( \mathbf{a} = \begin{pmatrix} a_1 \\ a_2 \end{pmatrix} \) be a nonzero vector in \( \mathbb{R}^2 \). Suppose our basis \( \mathcal{B} \) consists of the standard basis vectors: \[ \mathcal{B} = \left\{ \begin{pmatrix} 1 \\ 0 \end{pmatrix}, \begin{pmatrix} 0 \\ 1 \end{pmatrix} \right\} \] ### Step 2: Compute \( \tau_{\mathbf{a}} \) on Basis Vectors Next, we apply \( \tau_{\mathbf{a}} \) on the basis vectors: 1. For \( \mathbf{x}_1 = \begin{pmatrix} 1 \\ 0 \end{pmatrix} \): \[ \tau_{\mathbf{a}}(\mathbf{x}_1) = -\begin{pmatrix} 1 \\ 0 \end{pmatrix} + 2 \frac{\mathbf{a} \cdot \begin{pmatrix} 1 \\ 0 \end{pmatrix}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} \] The dot product \( \mathbf{a} \cdot \begin{pmatrix} 1 \\ 0 \end{pmatrix} = a_1 \) and \( \mathbf{a} \cdot \mathbf{a} = a_1^2 + a_2^2 \). Thus, \[ \tau_{\mathbf{a}}(\mathbf{x}_1) = -\begin{pmatrix} 1 \\ 0 \end{pmatrix} + 2 \cdot \frac{a_1}{a_1^2 + a_2^2} \begin{pmatrix} a_1 \\ a_2 \end{pmatrix} = \begin{pmatrix} -1 + \frac{2a_1^2}{a_1^2 + a_2^2} \\ \frac{2a_1a_2}{a_1^2 + a_2^2} \end{pmatrix} \] 2. For \( \mathbf{x}_2 = \begin{pmatrix} 0 \\ 1 \end{pmatrix} \): \[ \tau_{\mathbf{a}}(\mathbf{x}_2) = -\begin{pmatrix} 0 \\ 1 \end{pmatrix} + 2 \frac{\mathbf{a} \cdot \begin{pmatrix} 0 \\ 1 \end{pmatrix}}{\mathbf{a} \cdot \mathbf{a}} \mathbf{a} \] The dot product \( \mathbf{a} \cdot \begin{pmatrix} 0 \\ 1 \end{pmatrix} = a_2 \). Thus, \[ \tau_{\mathbf{a}}(\mathbf{x}_2) = -\begin{pmatrix} 0 \\ 1 \end{pmatrix} + 2 \cdot \frac{a_2}{a_1^2 + a_2^2} \begin{pmatrix} a_1 \\ a_2 \end{pmatrix} = \begin{pmatrix} \frac{2a_1a_2}{a_1^2 + a_2^2} \\ -1 + \frac{2a_2^2}{a_1^2 + a_2^2} \end{pmatrix} \] ### Step 3: Construct the Matrix The resulting vectors from applying \( \tau_{\mathbf{a}} \) to the basis vectors are now: \[ \tau_{\mathbf{a}}(\mathbf{x}_1) = \begin{pmatrix} -1 + \frac{2a_1^2}{a_1^2 + a_2^2} \\ \frac{2a_1a_2}{a_1^2 + a_2^2} \end{pmatrix}, \quad \tau_{\mathbf{a}}(\mathbf{x}_2) = \begin{pmatrix} \frac{2a_

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