🎓 Linear Algebra 🇬🇧 A-Level Further Maths 🌐 IB HL Mathematics 🎓 University

Matrix Determinant Calculator

Compute the determinant of any square matrix (2×2 to 5×5) with step-by-step working. Uses cofactor expansion for 2×2/3×3 and LU decomposition for larger matrices.

Quick Answer
2×2: det = ad − bc · 3×3: cofactor expansion · det = 0 → singular (no inverse) · det ≠ 0 → invertible · |det| = volume scaling factor.
Curriculum Coverage Method taught
🇬🇧 UK A-Level Further Maths 2×2 and 3×3Cofactor expansion, Sarrus rule
🌐 IB HL Mathematics 2×2 and 3×3Cofactor expansion (GDC allowed)
🇩🇪 Germany Abitur Up to 3×3Sarrus rule (preferred in Germany)
🇺🇸 US Linear Algebra n×n generalLU decomposition, row reduction
🇯🇵 Japan (数学C) 2×2 and 3×3Cofactor expansion
💻 ML / Numerical Computing n×nLU decomposition (numerically stable)

Properties of Determinants

  • det(AB) = det(A) × det(B) — product rule
  • det(Aᵀ) = det(A) — transpose has same determinant
  • det(A⁻¹) = 1 / det(A) — inverse determinant
  • det(kA) = kⁿ det(A) for n×n matrix A scaled by k
  • Swapping two rows negates the determinant
  • Adding a multiple of one row to another leaves the determinant unchanged

Frequently Asked Questions

What is the Sarrus rule and when is it used?

The Sarrus rule is a mnemonic for computing 3×3 determinants: write the matrix, repeat the first two columns to the right, then sum the three main diagonals (going down-right) and subtract the three anti-diagonals (going down-left). It is only valid for 3×3 and is popular in German, French, and Spanish high school curricula. It does NOT generalize to 4×4 or larger matrices — a common mistake is to attempt the "Sarrus method" on 4×4 matrices.

How is the determinant used in Cramer's rule?

Cramer's rule solves a linear system Ax = b by computing xᵢ = det(Aᵢ) / det(A), where Aᵢ is A with column i replaced by b. It requires det(A) ≠ 0 (non-singular) and is computationally expensive for large systems (O(n!) operations), so it's mainly used for 2×2 and 3×3 systems in exams. Gaussian elimination is preferred computationally.