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ExampleConstruction: AI-adaptedVerification: AI-generatedSession-authored (Fable 5 assisted)precheck passjudge pass (z-ai/glm-5.2)audited 2026-07-29
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  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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Every nonempty closed subset AA of R\mathbb{R} is the zero set of xd(x,A)x \mapsto d(x, A) and the intersection of the open sets {x:d(x,A)<1/(n+1)}\{x : d(x,A) < 1/(n+1)\}, worked for [0,1][0,1] and for {0}\{0\}

Example

Let R\mathbb{R} carry its usual metric dR(s,t)=std_{\mathbb{R}}(s,t) = |s-t| and its usual topology (The absolute value makes R\mathbb{R} a metric space: d(x,y)=xyd(x,y) = |x-y| is a metric, its open balls are the intervals (xr,x+r)(x-r, x+r), and it is unbounded, Metrizable space: a topological space whose topology is induced by some metric; metrizability is topological, the metric is not), and write 1/(n+1)1/(n+1) for the inverse of the canonical natural ι(n+1)\iota(n+1) (The canonical natural ι(n)=n1F\iota(n) = n \cdot 1_F of a field). Let ARA \subseteq \mathbb{R} be nonempty and closed, and put d(x,A):=inf{xa:aA}d(x,A) := \inf\{\, |x - a| : a \in A \,\} (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space). Then, as the general metric theorem (In a metric space every closed set is a zero set and a GδG_\delta, and the distance function separates a point from a closed set, so every metrizable space is Tychonoff and perfectly normal) specialises:

  1. xd(x,A)x \mapsto d(x,A) is continuous and A=Z(d(,A))A = Z(d(\cdot,A)) (Zero sets and cozero sets of continuous real-valued functions), so AA is a zero set.
  2. A=nN{xR:d(x,A)<1/(n+1)}A = \bigcap_{n \in \mathbb{N}} \{\, x \in \mathbb{R} : d(x,A) < 1/(n+1) \,\}, an intersection of open sets, so AA is a GδG_\delta of the topological space R\mathbb{R} (GδG_\delta and FσF_\sigma subsets of a topological space, agreeing with the real-line notion) and hence a GδG_\delta subset of R\mathbb{R} in the sense of FσF_\sigma and GδG_\delta subsets of R\mathbb{R}, the two notions being the same one.

Two worked instances:

  • A=[0,1]A = [0,1] (Intervals of R\mathbb{R}: the nine order-convex forms, nondegeneracy, and length). Here d(x,[0,1])={xx<000x1x1x>1d(x,[0,1]) = \begin{cases} -x & x < 0 \\ 0 & 0 \le x \le 1 \\ x - 1 & x > 1 \end{cases} so Z(d(,[0,1]))=[0,1]Z(d(\cdot,[0,1])) = [0,1] and, for every real ε>0\varepsilon > 0, {x:d(x,[0,1])<ε}=(ε, 1+ε)\{\, x : d(x,[0,1]) < \varepsilon \,\} = (-\varepsilon,\ 1 + \varepsilon). Taking ε=1/(n+1)\varepsilon = 1/(n+1) gives [0,1]  =  nN(1/(n+1), 1+1/(n+1)).[0,1] \;=\; \bigcap_{n \in \mathbb{N}} \big(-1/(n+1),\ 1 + 1/(n+1)\big).
  • A={0}A = \{0\}. Here d(x,{0})=xd(x,\{0\}) = |x|, so {0}  =  nN(1/(n+1), 1/(n+1)),\{0\} \;=\; \bigcap_{n \in \mathbb{N}} \big(-1/(n+1),\ 1/(n+1)\big), the standard presentation of a point of R\mathbb{R} as a GδG_\delta.

The converse fails. A GδG_\delta subset of R\mathbb{R} need not be closed: (0,1)(0,1) is open, hence a GδG_\delta by the constant sequence, and it is not closed.

Facts & Assumptions

Given: R\mathbb{R} with the usual metric and topology, a nonempty closed ARA \subseteq \mathbb{R}, and reals x,a,εx, a, \varepsilon with ε>0\varepsilon > 0.

[A1]

d(x,A)=inf{xa:aA}d(x,A) = \inf\{\, |x-a| : a \in A \,\} exists for nonempty AA, is a lower bound of that set, and is xa\le |x-a| for every aAa \in A; and any real that is a lower bound of the set is d(x,A)\le d(x,A) (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space, Greatest lower bound (infimum)).

[L1]

In a metric space every nonempty closed set AA satisfies A=Z(d(,A))A = Z(d(\cdot,A)) and A=n{x:d(x,A)<1/(n+1)}A = \bigcap_n \{x : d(x,A) < 1/(n+1)\}, and d(,A)d(\cdot,A) is continuous (In a metric space every closed set is a zero set and a GδG_\delta, and the distance function separates a point from a closed set, so every metrizable space is Tychonoff and perfectly normal, claims 1 and 2, d(x,A)d(y,A)d(x,y)|d(x,A) - d(y,A)| \le d(x,y), so the distance to a fixed nonempty set is 11-Lipschitz).

[L2]

The topological notions of GδG_\delta and FσF_\sigma for R\mathbb{R} with its usual topology coincide with those of FσF_\sigma and GδG_\delta subsets of R\mathbb{R}, the two collections of open subsets of R\mathbb{R} being one collection (GδG_\delta and FσF_\sigma subsets of a topological space, agreeing with the real-line notion, Open subset of R\mathbb{R} (every point has a neighbourhood inside it), closed subset (complement open), and clopen).

[L3]

s0|s| \ge 0, s=0|s| = 0 exactly when s=0s = 0, and for c>0c > 0 one has s<c|s| < c exactly when c<s<c-c < s < c (Basic properties of the absolute value).

[L4]

[0,1]={t:0t1}[0,1] = \{\, t : 0 \le t \le 1 \,\} and (u,v)={t:u<t<v}(u,v) = \{\, t : u < t < v \,\}; a two-element set of reals has a minimum (Intervals of R\mathbb{R}: the nine order-convex forms, nondegeneracy, and length, Maximum and minimum of a set).

Verification

technique · direct
1.1

Claims 1 and 2 are [L1] applied to the metric space R\mathbb{R} with dRd_{\mathbb{R}}, and the identification of the two readings of GδG_\delta is [L2].

L1L2
1.2

For x<0x < 0: every a[0,1]a \in [0,1] has a0>xa \ge 0 > x, so xa=ax|x - a| = a - x by [L3], and this is minimised over a[0,1]a \in [0,1] at a=0a = 0 with value x-x; since x-x belongs to the set and is a lower bound of it, d(x,[0,1])=xd(x,[0,1]) = -x by [A1].

A1L3L4
1.3

For 0x10 \le x \le 1: x[0,1]x \in [0,1] gives xx=0|x - x| = 0 in the set, and 00 is a lower bound by [L3], so d(x,[0,1])=0d(x,[0,1]) = 0 by [A1].

A1L3L4
1.4

For x>1x > 1: every a[0,1]a \in [0,1] has a1<xa \le 1 < x, so xa=xa|x-a| = x-a, minimised at a=1a = 1 with value x1x - 1, which lies in the set and is a lower bound; so d(x,[0,1])=x1d(x,[0,1]) = x-1 by [A1].

A1L3L4
1.5

The set (0,1)(0,1) is open, hence a GδG_\delta by [L5], and is not closed, so a GδG_\delta subset of R\mathbb{R} need not be closed.

L5
2.1

By steps 1.2, 1.3 and 1.4 the zero set of d(,[0,1])d(\cdot,[0,1]) is {x:0x1}=[0,1]\{x : 0 \le x \le 1\} = [0,1], since x>0-x > 0 for x<0x < 0 and x1>0x - 1 > 0 for x>1x > 1.

step 1.2step 1.3step 1.4L4
2.2

By steps 1.2, 1.3 and 1.4, for ε>0\varepsilon > 0 the condition d(x,[0,1])<εd(x,[0,1]) < \varepsilon holds exactly when x<ε-x < \varepsilon for x<0x < 0, always for 0x10 \le x \le 1, and x1<εx - 1 < \varepsilon for x>1x > 1; that is, exactly when ε<x<1+ε-\varepsilon < x < 1 + \varepsilon.

step 1.2step 1.3step 1.4L4
2.3

For A={0}A = \{0\} the set {xa:a{0}}\{\, |x - a| : a \in \{0\} \,\} is the single value x|x|, so d(x,{0})=xd(x,\{0\}) = |x| by [A1]; hence {x:d(x,{0})<1/(n+1)}=(1/(n+1), 1/(n+1))\{x : d(x,\{0\}) < 1/(n+1)\} = (-1/(n+1),\ 1/(n+1)) by [L3], and intersecting over nn gives {0}\{0\} by claim 2 of step 1.1.

step 1.1A1L3
3.1

Taking ε=1/(n+1)\varepsilon = 1/(n+1) in step 2.2 and intersecting over nNn \in \mathbb{N} gives [0,1]=n(1/(n+1), 1+1/(n+1))[0,1] = \bigcap_n (-1/(n+1),\ 1 + 1/(n+1)) by claim 2 of step 1.1.

step 1.1step 2.2
4.1

Steps 1.1, 3.1, 2.3 and 1.5 establish the two claims, the two worked instances and the failure of the converse.

step 1.1step 3.1step 2.3step 1.5

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