Matrix Multiplication Calculator

Multiply 2x2 and 3x3 matrices with step-by-step solutions and visual representations

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C = A × B, where C[i][j] = Σ A[i][k] × B[k][j]

Multiply two matrices using the dot product of rows and columns

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Quick Examples

Error

Result Matrix C = A × B

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Step-by-Step Calculation

Formula Reference

Element Formula
C[i][j] Σ A[i][k] × B[k][j]
2×2 Example C[1][1] = a₁₁b₁₁ + a₁₂b₂₁

Important Note

Matrix multiplication is NOT commutative: A × B ≠ B × A in general

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About Matrix Multiplication Calculator

What is Matrix Multiplication?

Matrix multiplication (also called the matrix product) is a binary operation that produces a new matrix from two input matrices. Unlike regular multiplication, the order matters — A × B generally does not equal B × A.

Matrix Multiplication Condition

For two matrices A and B to be multiplied (A × B), the number of columns in A must equal the number of rows in B:

  • If A is an m × n matrix
  • And B is an n × p matrix
  • Then C = A × B will be an m × p matrix

Matrix Multiplication Formula

Each element C[i][j] in the resulting matrix is calculated as the dot product of the i-th row of matrix A and the j-th column of matrix B:

C[i][j] = Σ A[i][k] × B[k][j] for k = 1 to n

2×2 Matrix Multiplication Example

For matrices A = [[a, b], [c, d]] and B = [[e, f], [g, h]]:

C = A × B = [[ae+bg, af+bh], [ce+dg, cf+dh]]

Step-by-Step Process

  1. Check dimensions: Verify that columns of A equal rows of B
  2. For each position (i,j): Take row i of A and column j of B
  3. Dot product: Multiply corresponding elements and sum them
  4. Place result: The sum becomes element C[i][j]

Key Properties

  • Not Commutative: A × B ≠ B × A (in general)
  • Associative: (A × B) × C = A × (B × C)
  • Distributive: A × (B + C) = A × B + A × C
  • Identity: A × I = I × A = A

Applications

  • Computer Graphics: Transformations, rotations, scaling
  • Machine Learning: Neural network operations
  • Physics: Quantum mechanics, coordinate transformations
  • Economics: Input-output models
  • Engineering: Systems of equations, state-space models