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The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
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On , abstract Cauchy–Schwarz is exactly the published finite-sum Cauchy–Schwarz inequality
Statement
For , Cauchy–Schwarz in the standard coordinate inner product is exactly
with equality exactly when the two lists are proportional in the symmetric sense. This includes .
Facts & Assumptions
Given: Real coordinate vectors .
The standard real coordinate pairing is , with (The standard formulas on and on are inner products).
Abstract Cauchy–Schwarz has equality exactly for linearly dependent vectors (Cauchy–Schwarz: , with equality exactly for linearly dependent vectors).
The published finite-sum theorem states the displayed inequality and equality exactly when some satisfies for every (The Cauchy-Schwarz inequality for finite sums).
Proof
Substituting [L1] into [L2] gives the displayed finite-sum inequality term for term.
Coordinate vectors are linearly dependent exactly when there is a nonzero scalar pair with for all , so the equality condition agrees with [L3]. For , both sides are zero and the empty lists satisfy the symmetric proportionality condition.
Depends on
- The standard formulas $\langle x,y\rangle=\sum_{k<n}x_k y_k$ on $\mathbb R^n$ and $\sum_{k<n}x_k\overline{y_k}$ on $\mathbb C^n$ are inner products
- Cauchy–Schwarz: $|\langle u,v\rangle|\leq\lVert u\rVert\lVert v\rVert$, with equality exactly for linearly dependent vectors
- The Cauchy-Schwarz inequality for finite sums
Used by
Nothing in the library uses this result yet.
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 64 results over 13 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., §6A (standard reference, not scraped)