Identity Matrix

Definition

The identity matrix is a special square matrix where all the elements on the main diagonal are 1, and all other elements are 0. It is denoted by the symbol $\mathbf{I}$ and serves as the multiplicative identity for matrix multiplication, similar to how the number 1 is the multiplicative identity for scalar multiplication.

5 Must Know Facts For Your Next Test

1. The identity matrix of size $n \times n$ is denoted as $\mathbf{I}_n$, where all the diagonal elements are 1, and all other elements are 0.
2. Multiplying any matrix $\mathbf{A}$ by the identity matrix $\mathbf{I}_n$ results in the original matrix $\mathbf{A}$, i.e., $\mathbf{A} \cdot \mathbf{I}_n = \mathbf{I}_n \cdot \mathbf{A} = \mathbf{A}$.
3. The identity matrix is the only matrix that is both an additive and a multiplicative identity for matrix operations.
4. The inverse of a square matrix $\mathbf{A}$ is denoted as $\mathbf{A}^{-1}$, and it satisfies the equation $\mathbf{A} \cdot \mathbf{A}^{-1} = \mathbf{A}^{-1} \cdot \mathbf{A} = \mathbf{I}_n$.
5. The identity matrix plays a crucial role in solving systems of linear equations using matrix inverses, as discussed in the topic 9.7 Solving Systems with Inverses.

Review Questions

• Describe the structure and properties of the identity matrix.
  • The identity matrix is a special square matrix where all the elements on the main diagonal are 1, and all other elements are 0. It is denoted by the symbol $\mathbf{I}$ and serves as the multiplicative identity for matrix multiplication, meaning that multiplying any matrix $\mathbf{A}$ by the identity matrix $\mathbf{I}_n$ results in the original matrix $\mathbf{A}$. The identity matrix is the only matrix that is both an additive and a multiplicative identity for matrix operations.
• Explain how the identity matrix is used in solving systems of linear equations.
  • The identity matrix plays a crucial role in solving systems of linear equations using matrix inverses, as discussed in the topic 9.7 Solving Systems with Inverses. If a square matrix $\mathbf{A}$ has an inverse $\mathbf{A}^{-1}$, then the equation $\mathbf{A} \cdot \mathbf{A}^{-1} = \mathbf{I}_n$ holds, where $\mathbf{I}_n$ is the identity matrix of the same size as $\mathbf{A}$. This property of the identity matrix allows us to solve systems of linear equations by multiplying both sides of the equation by the inverse of the coefficient matrix.
• Analyze the relationship between the identity matrix and the inverse of a square matrix.
  • The identity matrix $\mathbf{I}_n$ plays a crucial role in the concept of matrix inverses. If a square matrix $\mathbf{A}$ has an inverse, denoted as $\mathbf{A}^{-1}$, then the product of $\mathbf{A}$ and $\mathbf{A}^{-1}$ results in the identity matrix $\mathbf{I}_n$, i.e., $\mathbf{A} \cdot \mathbf{A}^{-1} = \mathbf{I}_n$. This property highlights the fact that the identity matrix is the only matrix that leaves other matrices unchanged when multiplied with them, making it the multiplicative identity for matrix operations. Understanding this relationship between the identity matrix and matrix inverses is crucial for solving systems of linear equations, as discussed in the topic 9.7 Solving Systems with Inverses.

Related terms

Square Matrix: A matrix with the same number of rows and columns, forming a square shape.

Diagonal Elements: The elements of a matrix that lie on the main diagonal, running from the top-left to the bottom-right corner.

Multiplicative Identity: A special element in a mathematical structure, such as a matrix or a number system, that leaves other elements unchanged when multiplied with them.