Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicableverified 2026-08-10 (gpt-5.6-terra-codex-subscription)
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.

Vector-valued functions f:A→Rm, their limits and continuity, with the dictionary to the metric notions

Definition

Throughout, m∈N with m≥1, and Rm carries the Euclidean norm ∥⋅∥2 of The Euclidean inner product ⟨x,y⟩=∑k<nxkyk on Rn and The p-norms ∥x∥p for rational p≥1, and ∥x∥∞, whose induced metric is the published d2 (Each ∥⋅∥p is a norm on Rn, and the induced metrics are exactly d1, d2 and d∞ of the published metric-spaces page, Rn as the set of functions n→R, and d1, d2, d∞ are metrics on it). A function into Rm is called vector-valued.

Continuity

Let (X,dX) be a metric space (Metric space: d(x,y)=0 iff x=y, symmetry, and the triangle inequality; pseudometric and ultrametric), let A⊆X carry the restricted metric dA (Isometry, isometric embedding, and the subspace metric on a subset), let f:A→Rm and let a∈A. Then f is continuous at a when

(∀ε>0) (∃δ>0) (∀x∈A) [ dX(x,a)<δ ⟹ ∥f(x)−f(a)∥2<ε ],

with ε,δ ranging over the positive reals, and continuous on A when it is continuous at every point of A.

This is not a new notion, and that is the point of writing it down. Since ∥f(x)−f(a)∥2=d2(f(x),f(a)) and dA is the restriction of dX, the displayed condition is verbatim the condition of Continuity of a map between metric spaces, at a point and globally, in the ε-δ form for the map of metric spaces f:(A,dA)→(Rm,d2). So every theorem about continuous maps of metric spaces applies to vector-valued functions with no translation, and this library has exactly one notion of continuity here. The same move was made once before, between the R-native and the metric notions, in Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace; this item is that move one dimension up in the codomain.

The two cases used below are X=R with dR(s,t)=∣s−t∣ (The absolute value makes R a metric space: d(x,y)=∣x−y∣ is a metric, its open balls are the intervals (x−r,x+r), and it is unbounded) and X=Rn with d2, for n≥1.

Limits, for a real domain

Let A⊆R, let f:A→Rm, let c be a limit point of A (Limit point, isolated point, adherent point, derived set, and dense subset of R) and let L∈Rm. We say f(x) tends to L as x tends to c, and write lim⁡x→cf(x)=L, when

(∀ε>0) (∃δ>0) (∀x∈A) [ 0<∣x−c∣<δ ⟹ ∥f(x)−L∥2<ε ].

This is the condition of The ε-δ limit lim⁡x→cf(x)=L of f:A→R at a limit point c of A with the absolute value in the codomain replaced by ∥⋅∥2; as there, the puncture 0<∣x−c∣ is what makes c a point the function need not be defined at, and the hypothesis that c is a limit point of A is what stops the condition from being satisfied vacuously.

The notation denotes: at most one L satisfies the condition. Suppose L and L′ both do and L≠L′. Then ε:=∥L−L′∥2/2>0 by (N1) for ∥⋅∥2 (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms). Take δ and δ′ for this ε and put η:=min⁡{δ,δ′}>0. Since c is a limit point of A there is x∈A with 0<∣x−c∣<η (Limit point, isolated point, adherent point, derived set, and dense subset of R), and then

∥L−L′∥2  ≤  ∥L−f(x)∥2+∥f(x)−L′∥2  <  ε+ε  =  ∥L−L′∥2

by (N3) and (N2), which trichotomy forbids. So L=L′.

Components

For i<m define the i-th coordinate projection πi:Rm→R by πi(y):=yi=y(i), and for f:A→Rm the i-th component fi:=πi∘f, a real-valued function on A.

Each πi is 1-Lipschitz (Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction): for y,z∈Rm,

∣πi(y)−πi(z)∣  =  ∣yi−zi∣  ≤  ∥y−z∥2  =  d2(y,z),

the middle inequality being ∣wi∣≤∥w∥2 at w:=y−z (The finite and reverse triangle inequalities for a norm; and for n≥1 every norm N on Rn satisfies N(x)≤C∥x∥1 and is Lipschitz, hence continuous, for d2 clause 3, or directly because wi2 is one term of the sum ∑k<mwk2). Written in coordinates, f(x) is the vector whose i-th coordinate is fi(x), and f(x)=∑i<mfi(x) ei in the standard basis (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).

Remarks

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Sources