Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-10
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.

Local comparison of a riemannian metric with the euclidean metric

Statement

For a compact set K contained in one coordinate chart of an n-dimensional Riemannian manifold, there are 0<cC< such that cv2gx(v,v)Cv2 for xK. The dimension-zero assertion is vacuous.

Facts & Assumptions

Given: A compact set K in a single chart.

[F1]

Coordinate criterion for a riemannian metric: A tensor g=i,jgijdxidxj is Riemannian exactly when its coordinate matrix G=(gij) has smooth entries and is symmetric positive definite. Under J=x/y it transforms by Gy=JTGxJ.

[F3]

A product of finitely many compact spaces is compact in the product topology: For every nN (def-natural-numbers) and every family (Xk)k<n of compact topological spaces (def-compact-space, def-topological-space), the product k<nXk with the product topology (def-product-topology) is compact. In particular a binary product X×Y of compact spaces is compact, and the empty product, a one-point space, is compact. No choice principle is used beyond lem-finite-choice, which is a theorem of ZF. That is what separates the finite case from the arbitrary one, where the Axiom of Choice is genuinely spent.

[F4]

A subset of Rn with the product topology is compact exactly when it is closed and bounded, the product topology being the Euclidean metric topology: Let nN with n1, let Rn be the set of functions nR (lem-metrics-on-rn) carrying the product topology of n copies of the usual topology of R (def-product-topology), and let d2 be the Euclidean metric. Then: 1. The product topology on Rn is the metric topology of d2 (def-metric-topology), so Rn as a product and Rn as a metric space are one topological space, and it is metrizable (def-metrizable-space). 2. A subset KRn is a compact subset for the product topology (def-compact-space) if and only if K is closed in Rn and bounded (def-metric-bounded-diameter). The hypothesis n1 is inherited from lem-metrics-on-rn, which defines Rn and its three metrics only there; for n=0 the product is a one-point space and is compact. No choice principle is used: the metric statement it is read off from is proved by bisection (thm-heine-borel-rn).

[F5]

A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value: Let (X,d) be a nonempty compact metric space (def-metric-compactness, def-metric-space) and let f:XR be continuous (def-metric-continuity), R carrying its usual metric dR(s,t)=st (lem-real-line-is-a-metric-space). Then the image f[X] is bounded above and below (def-bounded-set), and it has a maximum and a minimum (def-max-min): there are points xmax,xminX with f(xmin)    f(x)    f(xmax)for every xX, and then f(xmax)=supf[X] and f(xmin)=inff[X] (def-complete-ordered-field, def-infimum). Nonemptiness of X is a hypothesis and not an oversight: for X= the image is empty and has neither a supremum nor a maximum. No choice principle is used.

[F6]

For a metric space with its metric topology, compactness in the topological sense is compactness in the metric sense, and the two notions of compact subset coincide: Let (X,d) be a metric space (def-metric-space) and let Td be its metric topology (def-metric-topology), so that (X,Td) is a topological space (def-topological-space) and is metrizable (def-metrizable-space). Then: 1. (X,d) is a compact metric space (def-metric-compactness) if and only if (X,Td) is a compact topological space (def-compact-space). 2. For every AX: A is a compact subset of the metric space (X,d) if and only if A is a compact subset of the topological space (X,Td), the two readings of "compact subset" being the metric subspace (A,dA) (def-isometry-and-metric-embedding) and the topological subspace (A,(Td)A) (def-subspace-topology-top). Nothing here is a coincidence and nothing is transported. The open-cover condition of def-metric-compactness quantifies over families of subsets open in (X,d), and by def-metric-topology those are exactly the members of Td; so the two conditions are not merely equivalent, they are the same condition written twice. No choice principle is used.

Proof

technique · direct
1.1

If K is empty or n=0, take c=C=1. Otherwise K×Sn1 is nonempty and compact: the sphere is closed bounded in Euclidean space, and finite products preserve compactness. Euclidean product and metric topologies agree, so the compactness-agreement theorem makes it a compact metric space.

F3F4F6given
2.1

The function q(x,v)=vTG(x)v is continuous and strictly positive on that space. The extreme-value theorem gives an attained minimum c>0 and a finite maximum Cc. For v0, use v=v(v/v) and bilinearity to multiply these bounds by v2. For v=0 both inequalities are equalities. Thus the bounds hold on all tangent vectors over K.

F1F5step 1.1

Source locator

Lee, Chapter 13, pp.337–340, Proposition 13.25, Lemma 13.28 and Theorem 13.29; finite piecewise C1 refinements and pauses are treated explicitly here.

Depends on

Used by

Dependency tree · two levels

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Sources