GraphMath

QRF, Gram-Schmidt, part 3

Gradual orthogonalization as transformation of space

What do we learn by watching orthogonalization happen step by step?

This chapter shows Gram-Schmidt orthogonalization as a sequence of geometric updates rather than only as symbolic formulas. It tracks how the columns are orthogonalized in 2×2 and 3×3 cases, shows how R accumulates the inverse right-side updates and explains the role of shear and scaling matrices in building Q and R.

Key ideas

Gram-Schmidt can be understood as a sequence of localized geometric updates that change one column at a time.

  • Each subsequent matrix is obtained by right-multiplication Aₖ₊₁ = Aₖ Sₖ Dₖ, so one active column is changed at each step
  • The shear matrices remove overlap with earlier orthogonal directions, while the diagonal matrices normalize the remaining column
  • Q is produced by gradually removing scale and shear from A
  • R accumulates the removed scale and shear through the inverse right-side updates
  • The upper-triangular shape of R follows from the upper-triangular shape of every Sₖ, Dₖ and their inverses

This stepwise viewpoint makes QR factorization look like a sequence of transformations rather than a single final identity.

Why is gradual orthogonalization worth visualizing?

Because the usual symbolic formulas hide the fact that Gram-Schmidt changes one column at a time through specific geometric operations. The stepwise view shows exactly what is being removed, what is being normalized and how those updates accumulate into Q and R.

Related chapters

Chapter contents

The chapter is available as a PDF. Page links below are best-effort: most browsers support them but some viewers may ignore the page hint.

Topic Pages
Columns during orthogonalization (2×2) 1–2
Stepwise construction of R during orthogonalization (2×2) 3–4
Columns during orthogonalization (3×3) 5–7
Stepwise construction of R during orthogonalization (3×3) 7–10
What do we learn from gradual orthogonalization 10–12

Why does right-multiplication appear in this construction?

Because Gram-Schmidt changes columns, and right-multiplication is the natural way to update columns one at a time. Each shear or scaling matrix differs from the identity in one active column, so the sequence Aₖ₊₁ = Aₖ Sₖ Dₖ tracks the orthogonalization column by column.

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