- 9.20. The characteristic polynomial of a matrix A is p(λ) = −2³ — 32² - 6λ - 4. Find Tr(-2A) and det (-2A-¹). 9.21. The characteristic polynomial of a matrix 4 is n(2) 12 2 Find

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I'm encountering difficulties in solving this problem using matrix notation alone, and I'm seeking your assistance. The requirement is to find a solution using matrix notation exclusively, without utilizing any other methods. Could you kindly provide me with a detailed, step-by-step explanation using matrix notation to guide me towards the final solution?

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**Title: Understanding Matrix Operations: Trace and Determinant**

**Section: Worked Example - Matrix Expressions and Properties**

In this example, we explore properties of matrices using trace and determinant functions, specifically focusing on the expressions involving scalar multiplication and the inverse of a matrix.

**Example 9.20:**
\[ \text{Tr}(-2A) = 6, \quad \text{det}(-2A^{-1}) = 2. \]

Let's break this down:

1. **Trace of a Matrix** (`Tr`): 
   - The trace of a matrix \(A\), denoted as `Tr(A)`, is the sum of the elements on the main diagonal (the diagonal from the upper left to the lower right) of the matrix.
   - Here, we are given the trace of \(-2A\), which indicates that each element of the matrix \(A\) is first multiplied by \(-2\). The resulting trace of this transformed matrix is 6.

2. **Determinant of a Matrix** (`det`):
   - The determinant of a matrix \(A\), denoted as `det(A)`, is a scalar value that is a function of the entries of a square matrix. It can be interpreted as the volume scaling factor of the linear transformation described by the matrix.
   - Here, we are given the determinant of \(-2A^{-1}\), which indicates that the inverse of \(A\) is first multiplied by \(-2\). The determinant of this transformed matrix is 2.

**Practical Implications:**
- These exercises are fundamental in linear algebra, providing insights into how matrix operations affect properties like the trace and determinant.

By examining examples like this, students can improve their understanding of matrix manipulations, which are crucial for advanced studies in mathematics, physics, engineering, and computer science.

**End of Example.**
Transcribed Image Text:**Title: Understanding Matrix Operations: Trace and Determinant** **Section: Worked Example - Matrix Expressions and Properties** In this example, we explore properties of matrices using trace and determinant functions, specifically focusing on the expressions involving scalar multiplication and the inverse of a matrix. **Example 9.20:** \[ \text{Tr}(-2A) = 6, \quad \text{det}(-2A^{-1}) = 2. \] Let's break this down: 1. **Trace of a Matrix** (`Tr`): - The trace of a matrix \(A\), denoted as `Tr(A)`, is the sum of the elements on the main diagonal (the diagonal from the upper left to the lower right) of the matrix. - Here, we are given the trace of \(-2A\), which indicates that each element of the matrix \(A\) is first multiplied by \(-2\). The resulting trace of this transformed matrix is 6. 2. **Determinant of a Matrix** (`det`): - The determinant of a matrix \(A\), denoted as `det(A)`, is a scalar value that is a function of the entries of a square matrix. It can be interpreted as the volume scaling factor of the linear transformation described by the matrix. - Here, we are given the determinant of \(-2A^{-1}\), which indicates that the inverse of \(A\) is first multiplied by \(-2\). The determinant of this transformed matrix is 2. **Practical Implications:** - These exercises are fundamental in linear algebra, providing insights into how matrix operations affect properties like the trace and determinant. By examining examples like this, students can improve their understanding of matrix manipulations, which are crucial for advanced studies in mathematics, physics, engineering, and computer science. **End of Example.**
**Problem 9.20**

The characteristic polynomial of a matrix \( A \) is \( p(\lambda) = -\lambda^3 - 3\lambda^2 - 6\lambda - 4 \). Find \( \text{Tr}(-2A) \) and \( \det(-2A^{-1}) \).

---

**Explanation:**

In this problem, we are given the characteristic polynomial of a matrix \( A \) in the form \( p(\lambda) = -\lambda^3 - 3\lambda^2 - 6\lambda - 4 \). Using this information, we are asked to find the trace and the determinant of transformations of the matrix \( A \).

1. **Trace of a Matrix Transformation**:
   - The trace of a matrix \( A \), denoted by \( \text{Tr}(A) \), is defined as the sum of the elements on the main diagonal of \( A \).
   - For the transformation \( -2A \), the trace can be found by multiplying the sum of the diagonal elements of \( A \) by \(-2\).

2. **Determinant of a Matrix Transformation**:
   - The determinant of a matrix \( A \), denoted by \( \det(A) \), is a scalar value that is a function of the elements of \( A \). It can be interpreted as a volume scaling factor for the linear transformation described by the matrix.
   - For the transformation \( -2A^{-1} \), the determinant can be found by considering the properties of determinants for scalar multiples and inverse matrices.

These concepts are fundamental in linear algebra and are often utilized in various applications involving matrices.

---
Transcribed Image Text:**Problem 9.20** The characteristic polynomial of a matrix \( A \) is \( p(\lambda) = -\lambda^3 - 3\lambda^2 - 6\lambda - 4 \). Find \( \text{Tr}(-2A) \) and \( \det(-2A^{-1}) \). --- **Explanation:** In this problem, we are given the characteristic polynomial of a matrix \( A \) in the form \( p(\lambda) = -\lambda^3 - 3\lambda^2 - 6\lambda - 4 \). Using this information, we are asked to find the trace and the determinant of transformations of the matrix \( A \). 1. **Trace of a Matrix Transformation**: - The trace of a matrix \( A \), denoted by \( \text{Tr}(A) \), is defined as the sum of the elements on the main diagonal of \( A \). - For the transformation \( -2A \), the trace can be found by multiplying the sum of the diagonal elements of \( A \) by \(-2\). 2. **Determinant of a Matrix Transformation**: - The determinant of a matrix \( A \), denoted by \( \det(A) \), is a scalar value that is a function of the elements of \( A \). It can be interpreted as a volume scaling factor for the linear transformation described by the matrix. - For the transformation \( -2A^{-1} \), the determinant can be found by considering the properties of determinants for scalar multiples and inverse matrices. These concepts are fundamental in linear algebra and are often utilized in various applications involving matrices. ---
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