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Gram–Schmidt turns every finite independent list into an orthonormal list with the same successive spans
Statement
Let be a finite linearly independent list in a real or complex inner product space. There is an orthonormal list such that, for every ,
It is obtained recursively from
For , both lists are empty.
Facts & Assumptions
Given: A finite linearly independent list .
An orthonormal list is orthogonal and every listed vector has norm one (Orthogonal vectors and subspaces, orthogonal and orthonormal sets, and orthonormal bases).
A finite list is linearly independent when every list of scalars with has for all (Linear independence: a finite list is independent when forces every , and a subset is independent when every injective finite list into is independent).
For a nonzero vector , positive definiteness gives , so is defined and has norm one (The norm induced by a real or complex inner product).
Every finite orthogonal list of nonzero vectors is linearly independent (Every finite orthogonal list of nonzero vectors is linearly independent).
Proof
For there is nothing to construct, and the successive-span assertion at is equality of zero subspaces.
Suppose have been constructed orthonormally with the required span equalities. Define by the displayed formula. For , linearity and orthonormality give .
If , then lies in , say ; then the scalars for , and for satisfy with , contradicting the independence of through [L2]. Hence , and [L3] makes a unit vector orthogonal to its predecessors.
The formula for shows lies in , while its rearrangement shows lies in . Together with the induction hypothesis these give both inclusions in the span equality at .
Induction constructs the stated list and proves every successive-span equality. Its vectors are nonzero and orthogonal, so [L4] also confirms their independence; their unit norms make the list orthonormal.
Depends on
- Orthogonal vectors and subspaces, orthogonal and orthonormal sets, and orthonormal bases
- Every finite orthogonal list of nonzero vectors is linearly independent
- The norm $\lVert v\rVert=\sqrt{\langle v,v\rangle}$ induced by a real or complex inner product
- Linear independence: a finite list $v : n \to V$ is independent when $\sum_{i<n} \lambda_i v_i = 0_V$ forces every $\lambda_i = 0_F$, and a subset $S \subseteq V$ is independent when every injective finite list into $S$ is independent
Used by
- Every finite-dimensional real or complex inner product space has an orthonormal basis Corollary
- A worked QR factorisation of an invertible real matrix Example
- Gram–Schmidt on an explicit basis of ℂ² with conjugation visible Example
- Gram–Schmidt on an explicit basis of ℝ³ Example
- A Gram determinant is nonnegative and is positive exactly when the vector list is linearly independent Theorem
- Every invertible real or complex square matrix has a unique factorisation A=QR with Q orthogonal or unitary and R upper triangular with positive real diagonal Theorem
- For a subspace W of a finite-dimensional inner product space, V=W⊕ W^⊥ Theorem
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 63 results over 18 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Sheldon Axler, Linear Algebra Done Right, 4th ed., result 6.32 (standard reference, not scraped)
- Sergei Treil, Linear Algebra Done Wrong, §5.3.1 (standard reference, not scraped)