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TheoremStatement: AI-adaptedProof: AI-generatedSession-authored (Fable 5 assisted)precheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27
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Every open cover of a compact metric space has a Lebesgue number: a δ>0\delta > 0 such that every nonempty subset of diameter less than δ\delta lies inside a single member of the cover

Statement

Let (X,d)(X,d) be a compact metric space (Open cover, subcover, compact metric space, and compact subset of a metric space, Metric space: d(x,y)=0d(x,y) = 0 iff x=yx = y, symmetry, and the triangle inequality; pseudometric and ultrametric) and let U\mathcal{U} be an open cover of XX. Then there is a real δ>0\delta > 0, a Lebesgue number for U\mathcal{U}, such that every nonempty AXA \subseteq X with diam(A)<δ\operatorname{diam}(A) < \delta (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space) satisfies AUA \subseteq U for some UUU \in \mathcal{U}.

Diameters of nonempty subsets of XX are defined because a compact space is bounded (A compact subset of a metric space is closed and bounded) and a subset of a bounded set is bounded. No choice principle is used.

Facts & Assumptions

Given: A compact metric space (X,d)(X,d) and an open cover U\mathcal{U} of it.

[L2]

A compact metric space is bounded, and diam(A)=sup{d(u,v):u,vA}\operatorname{diam}(A) = \sup\{d(u,v) : u,v \in A\} is defined for every nonempty bounded AA (A compact subset of a metric space is closed and bounded, Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space).

[L3]

For nonempty SXS \subseteq X, d(x,S)=inf{d(x,y):yS}d(x,S) = \inf\{d(x,y) : y \in S\}; an infimum is a lower bound of its set and is at least every lower bound (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space, Greatest lower bound (infimum)).

[L5]

A continuous real-valued function on a nonempty compact metric space attains a least value (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value).

[L6]

A nonempty finite set of reals has a maximum, one of its members (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set).

Proof

technique · direct
1.1

If X=X = \emptyset then δ:=1\delta := 1 serves, there being no nonempty subset of XX to test; assume from now on XX \ne \emptyset.

L2
2.1

Compactness gives mNm \in \mathbb{N} and U0,,UmUU_0, \dots, U_m \in \mathcal{U} with X=U0UmX = U_0 \cup \dots \cup U_m.

L1step 1.1
3.1

If Ui=XU_i = X for some imi \le m, then δ:=1\delta := 1 serves again, every nonempty AXA \subseteq X being contained in that UiU_i; assume from now on that XUiX \setminus U_i \ne \emptyset for every imi \le m.

step 2.1
4.1

For α0,,αm\alpha_0, \dots, \alpha_m and β0,,βm\beta_0, \dots, \beta_m real one has αiβi+αiβimaxjβj+maxjαjβj\alpha_i \le \beta_i + |\alpha_i - \beta_i| \le \max_j \beta_j + \max_j|\alpha_j - \beta_j| for every ii, so maxiαimaxjβj+maxjαjβj\max_i \alpha_i \le \max_j \beta_j + \max_j |\alpha_j - \beta_j|, and by symmetry maxiαimaxiβimaxiαiβi|\max_i \alpha_i - \max_i \beta_i| \le \max_i |\alpha_i - \beta_i|.

L6step 3.1
5.1

Define g:XRg : X \to \mathbb{R} by g(x):=max{d(x,XUi):im}g(x) := \max\{\, d(x, X \setminus U_i) : i \le m \,\}, a maximum of a nonempty finite set of reals; each xd(x,XUi)x \mapsto d(x, X\setminus U_i) changes by at most d(x,y)d(x,y) between xx and yy, so by step 4.1 g(x)g(y)d(x,y)|g(x) - g(y)| \le d(x,y), and gg is Lipschitz with constant 11, hence continuous.

L4L6step 4.1
6.1

g(x)>0g(x) > 0 for every xXx \in X: such an xx lies in some UiU_i by step 2.1, openness gives a real r>0r > 0 with B(x,r)UiB(x,r) \subseteq U_i, so every yXUiy \in X \setminus U_i has d(x,y)rd(x,y) \ge r, making rr a lower bound of {d(x,y):yXUi}\{d(x,y) : y \in X \setminus U_i\} and hence g(x)d(x,XUi)r>0g(x) \ge d(x, X\setminus U_i) \ge r > 0.

L3L7step 2.1step 5.1
7.1

By the extreme value theorem applied to the nonempty compact XX and the continuous gg, there is xXx^{\ast} \in X with g(x)g(x)g(x^{\ast}) \le g(x) for every xx; put δ:=g(x)\delta := g(x^{\ast}), a real with δ>0\delta > 0 by step 6.1.

L5step 5.1step 6.1
8.1

Let AXA \subseteq X be nonempty with diam(A)<δ\operatorname{diam}(A) < \delta and fix aAa \in A; then g(a)δg(a) \ge \delta, so some imi \le m has d(a,XUi)δd(a, X \setminus U_i) \ge \delta, the maximum defining g(a)g(a) being one of its members, and the least such ii may be taken.

L2L6step 7.1
9.1

Every yAy \in A satisfies d(a,y)diam(A)<δd(a,XUi)d(a,y) \le \operatorname{diam}(A) < \delta \le d(a, X\setminus U_i), so yXUiy \notin X \setminus U_i, since a point of that set would make d(a,XUi)d(a,y)d(a, X\setminus U_i) \le d(a,y); hence AUiA \subseteq U_i with UiUU_i \in \mathcal{U}, and δ\delta is a Lebesgue number for U\mathcal{U}.

L2L3step 8.1

Remarks

What the lemma buys. An open cover gives, around each point, some member containing a ball about that point, with a radius depending on the point. A Lebesgue number is one radius that works everywhere at once, and that uniformity is exactly what turns pointwise continuity into uniform continuity in Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous.

Compactness is not removable. The cover of the interval (0,1)(0,1) by the intervals (1/(k+2),1)(1/(k+2), 1), kNk \in \mathbb{N}, has no Lebesgue number (The cover of (0,1)(0,1) by the intervals (1/(k+2),1)(1/(k+2), 1) has no Lebesgue number, so the Lebesgue number lemma needs compactness ), and (0,1)(0,1) is not compact.

The two degenerate cases in steps 1.1 and 3.1 are genuine. If XX is empty the conclusion is vacuous, and if some member of the finite subcover is the whole space the function gg of step 5.1 would call for the distance to the empty set, which this library leaves undefined (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space). Handling both separately costs two lines and avoids writing something undefined.

Depends on

Used by

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