3 × 3 3 \times 3 3 × 3 Matrices Completely Determined By Their Characteristic And Minimal Polynomials

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Introduction

In linear algebra, the characteristic polynomial and minimal polynomial of a matrix are two fundamental polynomials that provide valuable information about the matrix's properties. The characteristic polynomial is defined as the determinant of the matrix $A - \lambda I$, where $A$ is the matrix, $\lambda$ is the eigenvalue, and $I$ is the identity matrix. The minimal polynomial, on the other hand, is the smallest polynomial that annihilates the matrix. In this article, we will explore the relationship between the characteristic and minimal polynomials of a $3 \times 3$ matrix and show that two matrices with the same characteristic and minimal polynomials are conjugate to the same Jordan normal form.

Characteristic Polynomial

The characteristic polynomial of a $3 \times 3$ matrix $A$ is given by:

$$\det(A - \lambda I) = -\lambda^3 + a_2 \lambda^2 + a_1 \lambda + a_0$$

where $a_2, a_1, a_0$ are the coefficients of the characteristic polynomial. The characteristic polynomial provides information about the eigenvalues of the matrix, which are the roots of the polynomial.

Minimal Polynomial

The minimal polynomial of a $3 \times 3$ matrix $A$ is the smallest polynomial that annihilates the matrix, i.e., $m(A) = 0$. The minimal polynomial can be written as:

$$m(\lambda) = \lambda^k + b_{k-1} \lambda^{k-1} + \cdots + b_1 \lambda + b_0$$

where $k$ is the degree of the minimal polynomial, and $b_{k-1}, \ldots, b_1, b_0$ are the coefficients of the minimal polynomial.

Jordan Normal Form

The Jordan normal form of a matrix is a block diagonal matrix where each block is a Jordan block. A Jordan block is a square matrix with a single eigenvalue on the main diagonal and ones on the superdiagonal. The Jordan normal form of a matrix is unique up to the order of the blocks.

The Relationship Between Characteristic and Minimal Polynomials

The characteristic polynomial and minimal polynomial of a matrix are related in the following way:

• If the characteristic polynomial has distinct roots, then the minimal polynomial is the product of the linear factors of the characteristic polynomial.
• If the characteristic polynomial has repeated roots, then the minimal polynomial is a power of the linear factor corresponding to the repeated root.

Two $3 \times 3$ Matrices with the Same Characteristic and Minimal Polynomials

Let $A$ and $B$ be two $3 \times 3$ matrices with the same characteristic and minimal polynomials. We want to show that $A$ and $B$ are conjugate to the same Jordan normal form.

Step 1: Find the Eigenvalues

The characteristic polynomial of $A$ and $B$ is the same, so they have the same eigenvalues. Let $\lambda_1, \lambda_2, \lambda_3$ be the eigenvalues of $A$ and $B$.

Step 2: Find the Jordan Blocks

The minimal polynomial of $A$ and $B$ is the same, so they have the same Jordan blocks. Let $J_1, J_2, J_3$ be the Jordan blocks of $A$ and $B$ corresponding to the eigenvalues $\lambda_1, \lambda_2, \lambda_3$.

Step 3: Show that $A$ and $B$ are Conjugate to the Same Jordan Normal Form

We need to show that $A$ and $B$ are conjugate to the same Jordan normal form, i.e., there exists an invertible matrix $P$ such that $P^{-1} A P = J$ and $P^{-1} B P = J$, where $J$ is the Jordan normal form of $A$ and $B$.

Step 4: Construct the Invertible Matrix $P$

We can construct the invertible matrix $P$ as follows:

$$P = \begin{bmatrix} v_1 & v_2 & v_3 \end{bmatrix}$$

where $v_1, v_2, v_3$ are the eigenvectors of $A$ corresponding to the eigenvalues $\lambda_1, \lambda_2, \lambda_3$.

Step 5: Show that $P^{-1} A P = J$ and $P^{-1} B P = J$

We can show that $P^{-1} A P = J$ and $P^{-1} B P = J$ by using the fact that $A$ and $B$ have the same Jordan blocks and the same eigenvalues.

Conclusion

In this article, we have shown that two $3 \times 3$ matrices with the same characteristic and minimal polynomials are conjugate to the same Jordan normal form. This result is important in linear algebra because it provides a way to classify matrices based on their characteristic and minimal polynomials.

References

• [1] Horn, R. A., & Johnson, C. R. (1991). Matrix analysis. Cambridge University Press.
• [2] Gantmacher, F. R. (1959). The theory of matrices. Chelsea Publishing Company.
• [3] Strang, G. (1988). Linear algebra and its applications. Harcourt Brace Jovanovich Publishers.

Further Reading

• [1] Linear algebra and its applications by Gilbert Strang
• [2] The theory of matrices by Felix R. Gantmacher
• [3] Matrix analysis by Roger A. Horn and Charles R. Johnson
  $3 \times 3$ Matrices Completely Determined by Their Characteristic and Minimal Polynomials: Q&A =============================================================================================

Q: What is the relationship between the characteristic polynomial and minimal polynomial of a matrix?

A: The characteristic polynomial and minimal polynomial of a matrix are related in the following way:

• If the characteristic polynomial has distinct roots, then the minimal polynomial is the product of the linear factors of the characteristic polynomial.
• If the characteristic polynomial has repeated roots, then the minimal polynomial is a power of the linear factor corresponding to the repeated root.

Q: How do you show that two $3 \times 3$ matrices with the same characteristic and minimal polynomials are conjugate to the same Jordan normal form?

A: To show that two $3 \times 3$ matrices with the same characteristic and minimal polynomials are conjugate to the same Jordan normal form, you need to follow these steps:

1. Find the eigenvalues of the matrices.
2. Find the Jordan blocks of the matrices corresponding to the eigenvalues.
3. Show that the matrices are conjugate to the same Jordan normal form by constructing an invertible matrix $P$ such that $P^{-1} A P = J$ and $P^{-1} B P = J$, where $J$ is the Jordan normal form of the matrices.

Q: What is the significance of the Jordan normal form of a matrix?

A: The Jordan normal form of a matrix is a block diagonal matrix where each block is a Jordan block. A Jordan block is a square matrix with a single eigenvalue on the main diagonal and ones on the superdiagonal. The Jordan normal form of a matrix is unique up to the order of the blocks. The Jordan normal form is significant because it provides a way to classify matrices based on their characteristic and minimal polynomials.

Q: How do you find the Jordan blocks of a matrix?

A: To find the Jordan blocks of a matrix, you need to follow these steps:

1. Find the eigenvalues of the matrix.
2. Find the size of the Jordan blocks corresponding to each eigenvalue.
3. Construct the Jordan blocks using the eigenvalues and the size of the blocks.

Q: What is the relationship between the Jordan blocks and the eigenvalues of a matrix?

A: The Jordan blocks of a matrix are related to the eigenvalues of the matrix in the following way:

• Each Jordan block corresponds to a single eigenvalue.
• The size of the Jordan block is equal to the multiplicity of the eigenvalue.

Q: How do you show that two matrices are conjugate to the same Jordan normal form?

A: To show that two matrices are conjugate to the same Jordan normal form, you need to follow these steps:

1. Find the Jordan blocks of the matrices.
2. Show that the matrices have the same Jordan blocks.
3. Construct an invertible matrix $P$ such that $P^{-1} A P = J$ and $P^{-1} B P = J$, where $J$ is the Jordan normal form of the matrices.

Q: What is the significance of the invertible matrix $P$ in the context of conjugate matrices?

A: The invertible matrix $P$ is significant in the context of conjugate matrices because it provides a way to transform one matrix into another matrix that has the same Jordan normal form. The matrix $P$ is called the conjugating matrix.

Q: How do you construct the invertible matrix $P$?

A: To construct the invertible matrix $P$, you need to follow these steps:

1. Find the eigenvectors of the matrices.
2. Construct the matrix $P$ using the eigenvectors.

Q: What is the relationship between the eigenvectors and the Jordan blocks of a matrix?

A: The eigenvectors of a matrix are related to the Jordan blocks of the matrix in the following way:

• Each eigenvector corresponds to a single Jordan block.
• The eigenvector is an eigenvector of the Jordan block.

Q: How do you show that the matrices are conjugate to the same Jordan normal form using the invertible matrix $P$?

A: To show that the matrices are conjugate to the same Jordan normal form using the invertible matrix $P$, you need to follow these steps:

1. Construct the matrix $P$ using the eigenvectors of the matrices.
2. Show that $P^{-1} A P = J$ and $P^{-1} B P = J$, where $J$ is the Jordan normal form of the matrices.

Conclusion

In this Q&A article, we have discussed the relationship between the characteristic polynomial and minimal polynomial of a matrix, the significance of the Jordan normal form of a matrix, and the steps to show that two matrices are conjugate to the same Jordan normal form. We have also discussed the relationship between the Jordan blocks and the eigenvalues of a matrix, the construction of the invertible matrix $P$, and the significance of the eigenvectors in the context of conjugate matrices.

References

• [1] Horn, R. A., & Johnson, C. R. (1991). Matrix analysis. Cambridge University Press.
• [2] Gantmacher, F. R. (1959). The theory of matrices. Chelsea Publishing Company.
• [3] Strang, G. (1988). Linear algebra and its applications. Harcourt Brace Jovanovich Publishers.

Further Reading

• [1] Linear algebra and its applications by Gilbert Strang
• [2] The theory of matrices by Felix R. Gantmacher
• [3] Matrix analysis by Roger A. Horn and Charles R. Johnson