Linear Algebra, Live
Chapter 2 · Lesson 2 · Strang §2.2, §2.3, §2.6

Elimination and A = LU

How a computer solves Ax = b: subtract rows until the system is a triangle, solve from the bottom up, and record the steps as A = LU. 6 short slides, then worked examples and problems. Each slide has an everyday picture, a worked example and Python you can run right on the page.

Slides

01 · Strang §2.2 · The idea of elimination

Gaussian Elimination Explained Visually

How elimination solves two equations: subtract to remove an unknown, then back-substitute. A café puzzle, a worked example and live Python. Strang §2.2.

02 · Strang §2.2 · Pivots

Pivots and Back Substitution: 3×3 Elimination Step by Step

Clear one column at a time with the pivots, reach an upper triangular U, then solve from the bottom up. Worked 3×3 example with Python. Strang §2.2.

03 · Strang §2.2 · Breakdown of elimination

When Elimination Fails: Zero Pivots and Singular Systems

A zero pivot means swap rows or stop. See the three cases in the row picture: one solution, no solution, infinitely many. Strang §2.2.

04 · Strang §2.3 · Elimination using matrices

Elimination Matrices: Row Operations as Matrix Multiplication

Every elimination step is a matrix E. Multiplying by E subtracts a multiple of one row from another. Build E21 and E31 in Python. Strang §2.3.

05 · Strang §2.6 · Elimination = factorization

LU Decomposition Explained: Why A = LU

Elimination turns A into U, and the multipliers fill a lower triangular L so that A = LU. Factor once, solve many times. Python example. Strang §2.6.

06 · Recap · Reading

Lesson 2 Recap: Elimination and A = LU

Elimination in one page: multipliers and pivots, back substitution, zero pivots and row exchanges, elimination matrices, and the factorization A = LU.

✎ · Practice

Worked examples and problems

Worked examples and practice problems with hidden solutions: 2×2 and 3×3 elimination, pivots, zero pivots, elimination matrices and A = LU.