Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-29
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

The Euclidean inner product ⟨x,y⟩=∑k<nxkyk on Rn

Definition

Let n∈N. A natural number is a von Neumann natural, that is a set, and n={0,1,…,n−1} (The natural numbers N (von Neumann), On N the order is membership: m<n  ⟺  m∈n), so

Rn  =  { x  :  x is a function n→R }

is the function space of The vector space FX of all functions X→F with pointwise operations, and Fn as the case X=n={0,1,…,n−1} at F=R and X=n, a vector space over R under the pointwise operations (Vector space over a field). We write xk:=x(k) for k<n, and two elements of Rn are equal exactly when they agree at every k<n. This is the same set that Rn as the set of functions n→R, and d1, d2, d∞ are metrics on it calls Rn.

The Euclidean inner product of x,y∈Rn is the real number

⟨x,y⟩  :=  ∑k<nxk yk,

the finite sum of Finite sums and finite products, by recursion applied to the list k↦xkyk (extended by 0 beyond n, as every finite list in this library is). The Euclidean norm of x is

∥x∥2  :=  ⟨x,x⟩,

which is defined because ⟨x,x⟩=∑k<nxk2≥0 (a sum of nonnegative terms, Laws of finite sums and finite products clause 4 and Squares of nonzero elements are positive, the case xk=0 giving xk2=0 by Integer powers am) and every nonnegative real has a unique nonnegative square root (Square roots exist: a unique a≥0 with (a)2=a; the positives are {x2:x≠0}).

Both are defined for every n, including n=0

At n=0 the set R0 has exactly one element, the empty function, and it is the zero vector space (The standard list e:n→Fn with ei(i)=1F and ei(j)=0F for j≠i is an ordered basis of Fn; hence dim⁡FFn=n, and F0 is the zero space with basis ∅ and dimension 0 clause 5); the sum above is the empty sum, so ⟨x,y⟩=0 and ∥x∥2=0. This is the first place on this page where the two index regimes diverge, and the divergence is deliberate. The published metrics d1, d2, d∞ of Rn as the set of functions n→R, and d1, d2, d∞ are metrics on it are defined only for n≥1, because d∞ would otherwise be a maximum over the empty index set; the algebra above needs no such restriction. The boundary in this page runs between the algebra and the metric, not where a reader would guess, and Conventions of this page, the standing n≥1 hypothesis, and what is taken up elsewhere in the reading order lists exactly which items inherit n≥1.

The algebra of the inner product

For all x,y,z∈Rn and λ∈R:

  1. Symmetry. ⟨x,y⟩=⟨y,x⟩, since xkyk=ykxk termwise.
  2. Additivity in the first argument. ⟨x+y,z⟩=⟨x,z⟩+⟨y,z⟩: the list k↦(xk+yk)zk is the termwise sum of k↦xkzk and k↦ykzk, so Laws of finite sums and finite products clause 1 applies.
  3. Homogeneity in the first argument. ⟨λx,y⟩=λ⟨x,y⟩, by Laws of finite sums and finite products clause 2.
  4. Bilinearity. Clauses 2 and 3 together with symmetry give the same two laws in the second argument.
  5. Positive definiteness. ⟨x,x⟩≥0, and ⟨x,x⟩=0 if and only if x=0. Indeed a vanishing sum of nonnegative terms has every term 0 (Laws of finite sums and finite products clause 4), so xk2=0 for every k<n, and a nonzero real has a positive square (Squares of nonzero elements are positive), whence xk=0 for every k<n and x=0.
  6. Agreement with the published Euclidean metric. For n≥1 and x,y∈Rn, ∥x−y∥2=∑k<n(xk−yk)2=d2(x,y), the two sides being the same expression (Rn as the set of functions n→R, and d1, d2, d∞ are metrics on it). In particular ∥x∥2=d2(x,0).

That ∥⋅∥2 is a norm in the sense of A norm on a real vector space, the induced metric, and the dictionary with the metric axioms is proved in Cauchy-Schwarz ∣⟨x,y⟩∣≤∥x∥2∥y∥2 with its equality case, the triangle inequality for ∥⋅∥2, the parallelogram law and polarisation, where the triangle inequality is obtained from the Cauchy-Schwarz inequality; it is not assumed here.

Remarks

Depends on

Used by

…and 64 more results.

Dependency tree · two levels

78 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources