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- 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.
Every open cover of a compact metric space has a Lebesgue number: a such that every nonempty subset of diameter less than lies inside a single member of the cover
Statement
Let be a compact metric space (Open cover, subcover, compact metric space, and compact subset of a metric space, Metric space: iff , symmetry, and the triangle inequality; pseudometric and ultrametric) and let be an open cover of . Then there is a real , a Lebesgue number for , such that every nonempty with (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space) satisfies for some .
Diameters of nonempty subsets of 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 and an open cover of it.
is compact: every family of open subsets with union has a finite subfamily with union (Open cover, subcover, compact metric space, and compact subset of a metric space, A subset of a metric space is open in the subspace metric exactly when it is the trace of an open set of the ambient space, and it is compact as a metric space in its own right exactly when every family of open subsets of the ambient space covering it, indexed or not, has finitely many members covering it).
A compact metric space is bounded, and is defined for every nonempty bounded (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).
For nonempty , ; 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)).
For nonempty the map satisfies , so it is Lipschitz with constant , and a Lipschitz map is continuous (, so the distance to a fixed nonempty set is -Lipschitz, Lipschitz map, -Hölder map for rational , and contraction, Contraction implies Lipschitz implies uniformly continuous implies continuous; every Hölder map is uniformly continuous, and a Lipschitz map on a bounded space is Hölder for every exponent, Continuity of a map between metric spaces, at a point and globally, in the - form).
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).
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).
is open exactly when every point of has a ball around it inside (The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement, Open ball, closed ball and sphere in a metric space).
Proof
If then serves, there being no nonempty subset of to test; assume from now on .
Compactness gives and with .
If for some , then serves again, every nonempty being contained in that ; assume from now on that for every .
For and real one has for every , so , and by symmetry .
Define by , a maximum of a nonempty finite set of reals; each changes by at most between and , so by step 4.1 , and is Lipschitz with constant , hence continuous.
for every : such an lies in some by step 2.1, openness gives a real with , so every has , making a lower bound of and hence .
By the extreme value theorem applied to the nonempty compact and the continuous , there is with for every ; put , a real with by step 6.1.
Let be nonempty with and fix ; then , so some has , the maximum defining being one of its members, and the least such may be taken.
Every satisfies , so , since a point of that set would make ; hence with , and is a Lebesgue number for .
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 by the intervals , , has no Lebesgue number (The cover of by the intervals has no Lebesgue number, so the Lebesgue number lemma needs compactness ↗), and is not compact.
The two degenerate cases in steps 1.1 and 3.1 are genuine. If is empty the conclusion is vacuous, and if some member of the finite subcover is the whole space the function 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
- Open cover, subcover, compact metric space, and compact subset of a metric space
- A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value
- A compact subset of a metric space is closed and bounded
- $|d(x,A) - d(y,A)| \le d(x,y)$, so the distance to a fixed nonempty set is $1$-Lipschitz
- Lipschitz map, $\alpha$-Hölder map for rational $0 < \alpha \le 1$, and contraction
- Contraction implies Lipschitz implies uniformly continuous implies continuous; every Hölder map is uniformly continuous, and a Lipschitz map on a bounded space is Hölder for every exponent
- Continuity of a map between metric spaces, at a point and globally, in the $\varepsilon$-$\delta$ form
- Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space
- Greatest lower bound (infimum)
- Open ball, closed ball and sphere in a metric space
- The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement
- A subset of a metric space is open in the subspace metric exactly when it is the trace of an open set of the ambient space, and it is compact as a metric space in its own right exactly when every family of open subsets of the ambient space covering it, indexed or not, has finitely many members covering it
- Every nonempty finite set of reals has a maximum and a minimum
- Maximum and minimum of a set
- Metric space: $d(x,y) = 0$ iff $x = y$, symmetry, and the triangle inequality; pseudometric and ultrametric
Used by
- The cover of (0,1) by the intervals (1/(k+2), 1) has no Lebesgue number, so the Lebesgue number lemma needs compactness Counterexample
- The cover of [0,1] by (-1, 2/3) and (1/3, 2) has Lebesgue number 1/3, and no larger one Example
- Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous Theorem
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Sources
- Lebesgue's number lemma (Wikipedia) (standard reference, not scraped)
- J. Munkres, Topology, 2nd ed., §27 (standard reference, not scraped)