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TheoremStatement: Literature-sourcedProof: AI-adaptedSession-authored (Fable 5 assisted)precheck passjudge pass (z-ai/glm-5.2)verified 2026-07-26 (claude-opus-5)
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Zorn's lemma

Statement

Assume the Axiom of Choice (The Axiom of Choice). Let (P,)(P, \le) be a nonempty poset in which every chain has an upper bound. Then PP has a maximal element (Maximal element and greatest element).

Note the hypothesis asks only for an upper bound, not a least upper bound, and the conclusion asserts only that a maximal element exists, never that a greatest one does.

Facts & Assumptions

Given: A nonempty poset (P,)(P, \le) in which every chain has an upper bound, and the Axiom of Choice.

[A1]

PP \ne \emptyset, and every chain CPC \subseteq P has an upper bound in PP.

[A2]

Every family of nonempty sets has a choice function (The Axiom of Choice).

[L1]

A progressive map on a chain-complete poset has a fixed point (Bourbaki–Witt fixed point theorem).

[L2]

mm is maximal when there is no xx with m<xm < x (Maximal element and greatest element).

[L3]

uu is a strict upper bound of SS when s<us < u for every sSs \in S (Upper bound, least upper bound, and strict upper bound).

[L4]

The empty set is a chain, and a subset is a chain when any two of its elements are comparable (Chain in a poset).

[L5]

\le is a partial order, in particular transitive (uvu \le v and vwv \le w imply uwu \le w) and antisymmetric (uvu \le v and vuv \le u imply u=vu = v); the strict order u<vu < v means uvu \le v and uvu \ne v, so << is irreflexive (Partial order and partially ordered set).

[L6]

Inclusion is a partial order on any collection of sets: AAA \subseteq A; ABA \subseteq B and BAB \subseteq A give A=BA = B by extensionality; and ABCA \subseteq B \subseteq C gives ACA \subseteq C (Partial order and partially ordered set).

Proof

technique · contradiction
1.1

Suppose PP has no maximal element.

assume-contra
1.2

Let C\mathcal{C} be the set of all chains of PP, a subset of the power set of PP, partially ordered by inclusion.

L4L6construct
2.1

(C,)(\mathcal{C}, \subseteq) is a chain-complete poset: if DC\mathcal{D} \subseteq \mathcal{C} is a chain under inclusion then D\bigcup \mathcal{D} is a chain of PP, since any two of its elements lie in a common member of D\mathcal{D}, and it is the least upper bound of D\mathcal{D} under inclusion; the empty chain has least upper bound =\bigcup \emptyset = \emptyset, which is a chain.

step 1.2L4L6
2.2

For CCC \in \mathcal{C} let SCS_C be the set of strict upper bounds of CC in PP.

step 1.2L3construct
3.1

Each SCS_C is nonempty: CC has an upper bound uu in PP by hypothesis, taking any element of the nonempty PP when C=C = \emptyset; by assumption uu is not maximal, so there is vv with u<vu < v; then for every cCc \in C transitivity gives cvc \le v from cuvc \le u \le v, and cvc \ne v, since c=vc = v would give vuv \le u and uvu \le v, hence u=vu = v by antisymmetry, contradicting u<vu < v; so c<vc < v for every cCc \in C and vSCv \in S_C.

step 2.2step 1.1A1L2L3L5
4.1

Apply the Axiom of Choice to the family S={SC:CC}\mathcal{S} = \{S_C : C \in \mathcal{C}\}, every member of which is nonempty, obtaining a choice function gg with g(S)Sg(S) \in S for each SSS \in \mathcal{S}; composing with the map CSCC \mapsto S_C, which is a function on C\mathcal{C}, yields a selection Cg(SC)SCC \mapsto g(S_C) \in S_C defined for every chain CC, and no injectivity of CSCC \mapsto S_C is needed, since two chains with the same set of strict upper bounds simply receive the same chosen element.

step 3.1A2
5.1

Define f(C)=C{g(SC)}f(C) = C \cup \{g(S_C)\} for CCC \in \mathcal{C}; this is again a chain, because g(SC)g(S_C) is a strict upper bound of CC and so is comparable to every element of CC.

step 4.1step 2.2L3L4L5construct
6.1

ff is progressive for inclusion, since Cf(C)C \subseteq f(C) by construction.

step 5.1
7.1

By Bourbaki–Witt applied to the chain-complete C\mathcal{C} and the progressive ff, there is C0CC_0 \in \mathcal{C} with f(C0)=C0f(C_0) = C_0, that is g(SC0)C0g(S_{C_0}) \in C_0.

step 2.1step 6.1L1
8.1

But g(SC0)g(S_{C_0}) is a strict upper bound of C0C_0, so every element of C0C_0 is strictly below it, giving g(SC0)<g(SC0)g(S_{C_0}) < g(S_{C_0}), which is impossible because << is irreflexive.

step 7.1step 4.1L3L5discharge-contradiction

Remarks

  • The Axiom of Choice is used exactly once, at step 4.1, and nowhere else. Everything before it, including Bourbaki–Witt, is a theorem of ZF. That is why the fixed point theorem is kept as a separate item: it marks the boundary between what is free and what is bought.
  • The hypothesis is about all chains, including the empty one, whose upper bounds are exactly the elements of PP. So on this library's convention, where \emptyset is a chain (Chain in a poset), requiring every chain to have an upper bound already forces PP \ne \emptyset, and the nonemptiness hypothesis is stated separately for emphasis rather than as an independent assumption. In particular the empty poset does not satisfy the hypothesis: there the empty chain has no upper bound, because there is nothing at all to be one. Under the competing convention, on which chains are required to be nonempty, nonemptiness of PP is genuinely independent and cannot be dropped. See (N,)(\mathbb{N}, \le) has no maximal element: Zorn's chain hypothesis fails for the failure when unbounded chains exist.
  • The conclusion is maximal, not greatest, and conflating the two is the most common error in applying the lemma (FALSE: every maximal element is a greatest element).
  • The converse holds: Zorn's lemma implies the Axiom of Choice (Zorn's lemma implies the Axiom of Choice), so the two are equivalent over ZF (The Axiom of Choice and Zorn's lemma are equivalent).

Depends on

Used by

Dependency tree · next 3 levels

Direct dependencies and their dependencies through the next three levels: 17 results over 8 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.

Sources