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Gauss-Jordan elimination calculator

Reduce an augmented matrix with Gauss-Jordan elimination. See the reduced matrix, row operations, pivots and whether the system has one, no or many solutions.

Calculator

System status
Unique solution
Coefficient rank
2.0000000000
Reduced augmented matrix
RowEntries (constant last)
11, 0, 2
20, 1, 1
Row operations
StepOperation
0Scale each non-zero coefficient row by its largest coefficient magnitude
1Divide R1 by 1
2R2 = R2 - (1) R1
3Divide R2 by -2
4R1 = R1 - (1) R2
Unique solution
VariableValue
x12.000000
x21.000000

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How this calculator works

Enter one row per equation in row order, placing the constant after the coefficients. The algorithm scales non-zero coefficient rows, swaps for a large pivot, makes that pivot one, and eliminates its column above and below. A contradictory zero-coefficient row means no solution. Otherwise, a pivot for every variable gives a unique solution; missing pivots identify free variables. The relative threshold is 1e-12 after row scaling, so nearly dependent systems need higher-precision analysis.

Formula

For Ax = b, elementary row operations preserve solutions. Reduce [A|b] to pivots of one with zero entries above and below. A row [0 ... 0 | c], c != 0, is inconsistent.

Worked example

The equations x + y = 3 and x - y = 1 reduce to x = 2 and y = 1. For 2y = 4 and x = 3, a row swap gives x = 3 and y = 2.

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Frequently asked questions

How is this different from Gaussian elimination?

Gauss-Jordan elimination also clears entries above each pivot, so a unique solution can be read directly without back substitution.

What does a free variable mean?

A non-pivot variable can vary. Use the reduced rows to express pivot variables in terms of the free variables.

Is the result exact?

The method uses floating-point arithmetic with scaled pivoting. Ill-conditioned inputs can change rank decisions near the stated threshold.

Sources

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