Gauss-Jordan Calculator
Perform Gauss-Jordan elimination on augmented matrices [A|b]. Solve linear systems, find matrix inverses by augmenting with I, compare with Gaussian elimination, and understand partial pivoting and O(n³) complexity.
Solution (x1, x2, x3)
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Final RREF —
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Extended More scenarios, charts & detailed breakdown ▾
Solution
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Augmented RREF —
Professional Full parameters & maximum detail ▾
Solution & RREF
Solution —
RREF —
Algorithm Comparison
G-J vs Gaussian elimination —
Partial pivoting note —
Complexity —
How to Use This Calculator
- Enter augmented matrix [A|b] entries — solution and RREF appear instantly.
- Use Find Inverse tab to augment with I and extract A-inverse.
- Use Professional to compare with Gaussian elimination and learn about pivoting.
Formula
Row operations: (1) Swap rows, (2) Scale row by nonzero scalar, (3) Add multiple of one row to another.
Goal: produce RREF where pivot columns = identity.
Example
[[2,1,-1|8],[-3,-1,2|-11],[-2,1,2|-3]] → RREF → x1=2, x2=3, x3=-1.
Frequently Asked Questions
- An algorithm that applies row operations to an augmented matrix [A|b] to produce RREF. Unlike Gaussian elimination (which stops at REF), Gauss-Jordan fully reduces so the solution can be read directly.
- Augment A with the identity [A|I]. Apply row operations until the left side becomes I. The right side is then A-inverse. This uses 2n³/3 operations for an n×n matrix.
- At each column, swap rows so the largest absolute value is the pivot. This prevents division by small numbers and reduces numerical error.
- Gaussian elimination produces Row Echelon Form (zeros below pivots) then uses back-substitution. Gauss-Jordan goes further to RREF (zeros above and below each pivot), reading solutions directly.
- O(n³) for an n×n system. LU decomposition is preferred when solving Ax=b for many different b vectors, since it factorizes A once and solves each b in O(n²).
Related Calculators
Sources & References (5) ▾
- Introduction to Linear Algebra — Gilbert Strang — Wellesley-Cambridge Press
- OpenStax College Algebra — Gaussian Elimination — OpenStax
- MIT OCW 18.06 — Elimination with Matrices — MIT OpenCourseWare
- Khan Academy — Reduced Row Echelon Form — Khan Academy
- Numerical Recipes — LU Decomposition and Linear Systems — Cambridge University Press