LU Decomposition Steps Calculator

Break matrices into lower and upper triangular factors. Follow each pivot step with readable calculations. Practice matrix methods confidently using guided outputs and exports.

Calculator Form

Enter a square matrix, choose formatting options, and optionally include vector b to solve a full linear system.

Recommended for stability and zero-pivot avoidance.

Matrix A

Square matrix entries

Optional vector b

Solve Ax = b

Example Data Table

This sample matrix matches the default example and demonstrates how the page can also solve a system when vector b is supplied.

Row a₁ a₂ a₃ b
1 2 3 1 9
2 4 7 7 23
3 -2 4 5 12

Formula Used

Without pivoting, the factorization target is A = LU. With pivoting enabled, the target becomes PA = LU.

For Doolittle-style elimination, each multiplier is computed as mᵢₖ = Uᵢₖ / Uₖₖ. The calculator stores that multiplier in Lᵢₖ.

Each lower row is updated with Rᵢ = Rᵢ - mᵢₖRₖ. After all eliminations, the remaining matrix is upper triangular and becomes U.

When vector b is included, the page solves Ly = Pb first, then solves Ux = y to find the final unknown vector x.

How to Use This Calculator

  1. Choose a matrix size from 2 × 2 up to 6 × 6.
  2. Enter every value in matrix A using the generated input grid.
  3. Keep partial pivoting enabled for stronger numerical stability.
  4. Optionally fill vector b if you want a solved system.
  5. Press the calculate button to see matrices, steps, charts, and exports.

Frequently Asked Questions

1) What is LU decomposition?

It factors a square matrix into a lower triangular matrix and an upper triangular matrix. With pivoting, a permutation matrix is also used, so the relationship becomes PA = LU.

2) Why would I enable partial pivoting?

Pivoting swaps rows to avoid zero or tiny pivots. That improves numerical stability and lets the calculator handle more matrices that fail under plain LU decomposition.

3) Does every matrix have LU decomposition?

Not every matrix has a clean A = LU form without row swaps. Many still decompose successfully when permutation rows are allowed, giving PA = LU instead.

4) What do L and U represent?

L stores the elimination multipliers below the diagonal. U stores the updated upper triangular coefficients after each elimination step.

5) Can this page solve linear systems too?

Yes. Enter the right-hand-side vector b and the page performs forward substitution and backward substitution after factorization to estimate x in Ax = b.

6) How is the determinant calculated?

The determinant comes from the product of U's diagonal entries, adjusted for row-swap parity when pivoting is active.

7) Why is reconstruction error useful?

It compares the factored form with the permuted original matrix. Small error means the computed factors reproduce the input accurately.

8) What matrices work best here?

Square numeric matrices from 2×2 through 6×6 work best here. Extremely ill-conditioned inputs can still suffer rounding effects.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.