Identity Matrix

Clear explanation of the identity matrix with definitions, structure, and examples showing matrices where all diagonal entries are 1 and all other elements are zero.

1. What Is an Identity Matrix?

An identity matrix is a special type of scalar matrix in which all diagonal entries are 1 and every off-diagonal entry is 0. It is the matrix equivalent of the number 1 in ordinary multiplication.

An identity matrix of order n × n is denoted by \( I_n \).

In general:

\( I_n = \begin{bmatrix} 1 & 0 & 0 & \cdots & 0 \\ 0 & 1 & 0 & \cdots & 0 \\ 0 & 0 & 1 & \cdots & 0 \\ \vdots & \vdots & \vdots & \ddots & \vdots \\ 0 & 0 & 0 & \cdots & 1 \end{bmatrix} \)

2. Understanding the Structure of an Identity Matrix

The identity matrix is always a square matrix. Its key features are:

  • The main diagonal contains all 1s.
  • Every non-diagonal position contains 0.
  • Its form never changes — only its size (order) changes.

2.1. Examples of Identity Matrices

  • Identity matrix of order \( 1 \times 1 \):

    \( I_1 = [1] \)

  • Identity matrix of order \( 2 \times 2 \):

    \( I_2 = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} \)

  • Identity matrix of order \( 3 \times 3 \):

    \( I_3 = \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix} \)

2.2. Visual Pattern

The ones run diagonally from the top-left corner to the bottom-right. Everything else is zero. This pattern remains the same no matter how large the matrix becomes.

3. How to Identify an Identity Matrix

A matrix is an identity matrix if and only if:

  • It is square.
  • Every main diagonal entry is 1.
  • Every other entry is 0.

Even a single diagonal entry not equal to 1 makes the matrix not an identity matrix.

4. Why the Identity Matrix Is Important

The identity matrix behaves like the number 1 in matrix multiplication:

\( I_n A = A I_n = A \)

No matter which side it is multiplied on, it leaves the other matrix unchanged.

Some important uses of the identity matrix include:

  • Defining the inverse of a matrix.
  • Solving systems of linear equations.
  • Expressing matrix transformations.
  • Building concepts like eigenvalues, diagonalisation, and vector spaces.

Because of this special behaviour, the identity matrix plays a central role throughout linear algebra.