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Matrix Calculator

Perform matrix operations including addition, multiplication, determinant, and inverse

Matrix Operations

Matrix A

Matrix B

How to Use the Matrix Calculator

Getting Started

  • Step 1: Select the matrix operation you want to perform
  • Step 2: Choose the matrix size (2×2, 3×3, or 4×4)
  • Step 3: Enter the matrix elements (numbers only)
  • Step 4: For two-matrix operations, fill in both matrices
  • Step 5: Click Calculate to see the result and steps

Matrix Operations

  • Addition: Adds corresponding elements of two matrices
  • Multiplication: Matrix product following row-column rule
  • Determinant: Scalar value that characterizes the matrix
  • Inverse: Matrix A⁻¹ such that A × A⁻¹ = I
  • Transpose: Flips matrix over its diagonal

Key Concepts

  • Square Matrix: Same number of rows and columns
  • Identity Matrix: Square matrix with 1s on diagonal, 0s elsewhere
  • Singular Matrix: Matrix with determinant = 0 (no inverse)
  • Eigenvalues: Special scalars associated with linear transformations

Applications

  • Linear Systems: Solving systems of linear equations
  • Transformations: Geometric transformations in computer graphics
  • Physics: Quantum mechanics and state transformations
  • Economics: Input-output models and optimization

Frequently Asked Questions

When can I multiply two matrices?

Matrix multiplication A × B is possible when the number of columns in A equals the number of rows in B. The result has dimensions (rows of A) × (columns of B).

Why does my matrix have no inverse?

A matrix has no inverse when its determinant is zero (singular matrix). This means the matrix transformation is not reversible.

What is the determinant used for?

The determinant tells us if a matrix is invertible (det ≠ 0), the scaling factor of the linear transformation, and orientation preservation (positive vs negative determinant).

How accurate are the calculations?

The calculator uses double-precision floating-point arithmetic, providing accuracy to about 15 decimal places. For very large matrices or ill-conditioned problems, numerical errors may accumulate.

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