Alphabeta Math
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.

✓ 18 results · all verified · 12 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 6 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Continuity, IVT, EVT, and Uniform Continuity

1 · Prerequisites

2 · Summary

Objective. This page defines continuity of a real function on a subset of R, proves the toolkit that makes the notion usable, and then proves the four theorems that continuity exists for: the image of a compact set is compact, the extreme value theorem, the intermediate value theorem, and Heine-Cantor. Along the way it states the dictionary that reconciles the vocabulary of this page with the metric-space vocabulary of the earlier topology track, and it closes with counterexamples showing that compactness is needed for the extreme-value and uniform-continuity conclusions; the intermediate value theorem instead rests on the interval/connectedness hypothesis.

The definition, and the clause that is easy to get wrong. Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point says that f:A→R is continuous at c∈A when for every real ε>0 there is a real δ>0 with ∣f(x)−f(c)∣<ε for every x∈A satisfying ∣x−c∣<δ. Note the two differences from the limit of the previous page: the point c is required to lie in A, and the condition is unpunctured, so x=c is allowed. Three clauses follow, and all three are part of the definition. At a limit point of A, continuity at c is exactly lim⁡x→cf(x)=f(c); at an isolated point of A every function is continuous, because the only admissible x is c itself; and continuity on A is continuity at each point of A. The second clause is not the vacuous formula that FALSE: a function has at most one limit at every point of its domain, isolated points included warns about: there the punctured formula was satisfied by every real L at once and so defined nothing, whereas here the condition names one well-defined property, and the symbol lim⁡x→cf(x) simply does not exist at an isolated point.

Choice hygiene, and why it shapes the page. f is continuous at c∈A if and only if f(xk)→f(c) for every sequence in A converging to c, the converse direction costing countable choice proves that f is continuous at c if and only if f(xk)→f(c) for every sequence in A converging to c — sequences that may hit c, which is the difference from Heine criterion: lim⁡x→cf(x)=L iff f(xk)→L for every sequence in A∖{c} converging to c and what makes the criterion meaningful at an isolated point. The direction from continuity to sequences is a theorem of ZF; the converse inherits the single use of countable choice made on the previous page, and The sequence-to-ε direction of the Heine criterion uses countable choice for R, and where this library records that cost records exactly what is and is not claimed about that. As on that page, everything provable from ε and δ is proved that way: the algebra of continuous functions, composition, the preimage characterisation and the intermediate value theorem spend no choice at all. The two items that do spend it, Heine-Cantor in R: a continuous real function on a compact subset of R is uniformly continuous and the converse direction of the sequential criterion, say so in their own statements.

The toolkit. Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function proves that sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, and adds the clause the rest of the page uses constantly: constants, the identity, every power x↦xn and every polynomial function are continuous on every subset of R. A composite of continuous functions is continuous, with no side hypothesis of the kind the composition of limits needs proves that a composite of continuous functions is continuous with no side hypothesis — in contrast with Composition of limits holds under either hypothesis: f is defined at L with value M, or g avoids L on a punctured neighbourhood of c, which needs one of two extra conditions and is false without both (FALSE: lim⁡x→cf(g(x))=M whenever lim⁡x→cg=L and lim⁡y→Lf=M). The reason is visible in one line: the unpunctured quantifier of Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point controls f at the very value the limit version cannot see. f:A→R is continuous on A if and only if the preimage of every open subset of R is the intersection with A of an open subset of R, and dually for closed sets then gives the topological form: f is continuous on A exactly when the preimage of every open set is the trace on A of an open subset of R, and dually for closed sets. The preimage lives in A, not in R, so this does not say that preimages of open sets are open; and the witnessing open set is built as a single union over a family cut out by a property, so no choice function on an arbitrary subset of R is needed.

Compactness, and the two theorems it buys. The image of a compact subset of R under a continuous real function is compact proves that the image of a compact subset of R under a continuous function is compact, by an R-native cover argument in which the only selection is from a finite list. A continuous real function on a compact subset of R is bounded reads off boundedness, and Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value reads off attainment: on a nonempty compact K a continuous f satisfies sup⁡f[K]=f(p) and inf⁡f[K]=f(q) for some p,q∈K. The two ingredients are kept apart in that proof — compactness enters only through compactness of the image, order-completeness only through the existence of sup⁡ and inf⁡, and closedness of the image is the bridge.

The intermediate value theorem, by a canonical bisection. Intermediate value theorem, by bisection with a canonical left-half rule: a continuous function on [a,b] takes every value between f(a) and f(b) proves that a continuous function on [a,b] takes every value between f(a) and f(b). The bisection tests the left half first and takes the right half only when the left is excluded, so the passage from one interval to the next is a function of that interval and The recursion theorem applies with nothing selected; A nested sequence of nonempty closed bounded intervals has nonempty intersection, and the intersection is a single point exactly when the lengths tend to 0 then supplies the point, and only the choice-free direction of the sequential criterion is used to pass to the limit. The image of an interval under a continuous real function is order-convex, hence an interval, and the image of a closed bounded interval is a closed bounded interval draws the two standard consequences: the image of an order-convex set is order-convex, hence connected (A subset of R is connected if and only if it is order-convex, that is, an interval), and the image of a closed bounded interval is a closed bounded interval. Every continuous map of a closed bounded interval into itself has a fixed point is the third: a continuous map of [a,b] into itself has a fixed point, because φ(x)−x changes sign. The existence of k-th roots is not restated here: Existence and uniqueness of n-th roots: a unique a1/n≥0 with (a1/n)n=a already proves it, and the companion page's The intermediate value theorem gives a second proof that every nonnegative real has an n-th root, applied to xn on a closed bounded interval records the second proof without minting a second name for the same statement.

A converse worth having. A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous proves that a function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous. It needs no one-sided limits of monotone functions, which are not available at this point in the reading order; the whole proof reads the required δ off the image. It is stated as a standalone lemma so that a later page may cite it — the classical application is a monotone function built by a limiting construction whose image is known independently.

Uniform continuity, and the dictionary. Uniform continuity of f:A→R: one δ serving every pair of points of A asks for one δ serving every pair of points of A; the whole content is that ∃δ moves to the left of the point quantifier. Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace is then the hinge of the page. It proves that, for A⊆R with d(x,y)=∣x−y∣, continuity and uniform continuity in the senses defined here coincide with Continuity of a map between metric spaces, at a point and globally, in the ε-δ form and Uniform continuity of a map of metric spaces: one δ serving every point; that the Lipschitz and Hölder conditions for a real function are Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction instantiated, and are not redefined here; and — the clause that closes a seam nobody had flagged — that a subset of R is compact in the open-cover sense of Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset exactly when it is a compact metric subspace, with the same agreement for sequential compactness. Two consequences are recorded: the implications of 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 transfer verbatim to real functions, and Cauchy sequences of A are the same objects in both vocabularies.

Why three theorems are stated twice. The continuous image of a compact set, the extreme value theorem and Heine-Cantor appear on this page in R-native form and on the metric-spaces page in metric-general form, with distinct identifiers and distinct proofs. That is deliberate. The proofs here run through A subset of R is compact if and only if it is closed and bounded and A subset of R is compact iff it is sequentially compact, which are order-based; the metric proofs run through the cover machinery of metric spaces. Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace is the single place in the library where the duplication is acknowledged, and each duplicated item links it.

Heine-Cantor, extension, and the two sharp statements. Heine-Cantor in R: a continuous real function on a compact subset of R is uniformly continuous proves that a continuous function on a compact K⊆R is uniformly continuous, by contradiction from sequential compactness, with countable choice used exactly once and named. A uniformly continuous real function on a subset D⊆R extends uniquely to a uniformly continuous function on the closure of D proves that a uniformly continuous function on a nonempty D⊆R extends uniquely to a uniformly continuous function on D‾; that is the statement later pages need in order to define a function on the rationals first and pass to the reals. If ∣f(x)−f(y)∣≤C∣x−y∣α on an interval for some rational α>1 then f is constant explains why Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction stops at exponent 1: on an interval, an inequality ∣f(x)−f(y)∣≤C∣x−y∣α with rational α>1 forces f to be constant. Finally Rudin 4.20, the sharp converse: on a noncompact E⊆R there is an unbounded continuous function and a bounded continuous function with no greatest value, and if E is bounded there is a continuous function on E that is not uniformly continuous is the sharp converse to everything above: on a set that is not compact there is always an unbounded continuous function and a bounded continuous function whose supremum is not attained, and if that set is bounded there is also a continuous function that is not uniformly continuous. All four witness functions are exhibited explicitly.

The three false statements on this page each carry their own witness, verified in full: that continuity implies uniform continuity (FALSE: every continuous real function is uniformly continuous on its domain, refuted by 1/x on (0,1)), that a continuous image of a closed set is closed (FALSE: the image of a closed subset of R under a continuous real function is closed, refuted by 1/(1+x2) on R, whose image is (0,1]), and that boundedness of the domain suffices for the extreme value theorem (FALSE: a continuous real function on a bounded domain attains a greatest value, refuted by the identity on (0,1)). The companion page works the first and the third out again in more detail and adds the witnesses for the regularity hierarchy, the Dirichlet function, and the two examples that turn the intermediate value theorem into a computation.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point

Definition

Throughout, R is the complete ordered field with its order and absolute value (Complete ordered field (least-upper-bound property), Basic properties of the absolute value), and neighbourhoods are those of The ε-neighbourhood and the punctured ε-neighbourhood of a point of R.

Let A⊆R, let f:A→R and let c∈A. Then f is continuous at c when

(∀ε>0) (∃δ>0) (∀x∈A) [ ∣x−c∣<δ ⟹ ∣f(x)−f(c)∣<ε ],

with ε and δ ranging over the positive reals. In the language of neighbourhoods: for every real ε>0 there is a real δ>0 with

f(A∩Nδ(c))  ⊆  Nε(f(c)).

f is continuous on A when it is continuous at every point of A.

The point c is required to lie in A, and the condition is unpunctured. Both differ from The ε-δ limit lim⁡x→cf(x)=L of f:A→R at a limit point c of A, and deliberately. There the quantifier runs over 0<∣x−c∣<δ, which removes x=c; here x=c is allowed, and at x=c the implication reads ∣f(c)−f(c)∣=0<ε, which is automatic. So allowing x=c costs nothing, and it is what lets the definition be stated at every point of A, including the points where no limit exists.

Three clauses, and all three are part of the definition.

  1. At a limit point. Suppose c∈A is a limit point of A (Limit point, isolated point, adherent point, derived set, and dense subset of R). Then f is continuous at c if and only if the limit of f at c exists and lim⁡x→cf(x)  =  f(c) (The ε-δ limit lim⁡x→cf(x)=L of f:A→R at a limit point c of A). Indeed, for a given ε>0 a δ witnessing continuity witnesses the limit condition, because the limit condition quantifies over a subset of the points continuity quantifies over; and conversely a δ witnessing lim⁡x→cf(x)=f(c) witnesses continuity, because the one point it omits, x=c, satisfies ∣f(c)−f(c)∣<ε anyway.

  2. At an isolated point. Suppose c∈A is an isolated point of A (Limit point, isolated point, adherent point, derived set, and dense subset of R), so that Nη(c)∩A={c} for some real η>0. Then every f:A→R is continuous at c: take δ:=η, so that the only x∈A with ∣x−c∣<δ is c itself, and ∣f(c)−f(c)∣=0<ε.

  3. On a set. Continuity on A is continuity at each point of A, and nothing more. It is not a condition relating f to points outside A.

Every point of A is either a limit point of A or an isolated point of A, and never both (Limit point, isolated point, adherent point, derived set, and dense subset of R), so clauses 1 and 2 between them describe continuity at every point of A.

This is not the raw ε-δ formula of FALSE: a function has at most one limit at every point of its domain, isolated points included. That item records what goes wrong when the punctured formula of The ε-δ limit lim⁡x→cf(x)=L of f:A→R at a limit point c of A is written down at an arbitrary point of the domain: at an isolated point it is satisfied vacuously by every real L at once, so it defines nothing, and this library therefore leaves lim⁡x→cf(x) undefined at an isolated point. Continuity at an isolated point is a different matter: the formula above is not vacuous — it is a genuine condition on f(c), satisfied because f(c) is the only value being compared with itself — and it names a single, well-defined property. The limit is undefined there; the continuity is defined, and is automatic. Clause 1 is the only place where the two notions meet, and it is stated only where the limit exists as a notion.

Where the distinction disappears. If A is an open subset of R (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen), then every c∈A has some Nη(c)⊆A, and a punctured neighbourhood is never empty (The ε-neighbourhood and the punctured ε-neighbourhood of a point of R), so every point of A is a limit point of A and clause 1 covers the whole of A. The same holds when A is a nondegenerate interval (Intervals of R: the nine order-convex forms, nondegeneracy, and length). Isolated points are what force clause 2 to exist at all, and they occur as soon as A is allowed to be an arbitrary subset of R, as in A={0}∪[1,2].

Remarks

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passverified 2026-08-09 (gpt-5.6-terra-codex-subscription)Open item page →

f is continuous at c∈A if and only if f(xk)→f(c) for every sequence in A converging to c, the converse direction costing countable choice

Statement

Let A⊆R, let f:A→R and let c∈A. The following are equivalent.

  1. f is continuous at c (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).
  2. For every sequence (xk)k∈N with xk∈A for every k and xk→c (Sequences of reals: bounded, eventually, frequently, tails, subsequences, Limits and Cauchy sequences of reals), the sequence (f(xk))k∈N converges to f(c).

The sequences here are not required to avoid c, which is the one difference from Heine criterion: lim⁡x→cf(x)=L iff f(xk)→L for every sequence in A∖{c} converging to c and is exactly what makes the criterion available at an isolated point of A, where no limit exists.

The two directions do not cost the same. The implication from 1 to 2 is proved in ZF: the sequence is handed to the proof and nothing is selected. The implication from 2 to 1 is obtained below from Heine criterion: lim⁡x→cf(x)=L iff f(xk)→L for every sequence in A∖{c} converging to c, and therefore inherits the one use of the axiom of countable choice (The Axiom of Countable Choice (ACω)) made in that theorem's converse direction. What this library does and does not claim about that cost is recorded once, in The sequence-to-ε direction of the Heine criterion uses countable choice for R, and where this library records that cost, and is not restated here.

Nothing else on this page is routed through this theorem. The algebra of continuous functions, composition, the intermediate value theorem, the extreme value theorem and Heine-Cantor are all proved from ε and δ, or from compactness, exactly as the previous page organised itself. The choice-free direction 1 to 2 is used, in the intermediate value theorem and in Heine-Cantor, and each of those two items says which direction it uses.

Facts & Assumptions

Given: A set A⊆R, a function f:A→R and a point c∈A.

[L1]

Continuity at c: for every real ε>0 there is a real δ>0 such that every x∈A with ∣x−c∣<δ satisfies ∣f(x)−f(c)∣<ε (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

[L2]

A point of A is either a limit point of A or an isolated point of A, and never both; c is isolated in A when Nη(c)∩A={c} for some real η>0 (Limit point, isolated point, adherent point, derived set, and dense subset of R, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L4]

Heine criterion for limits: at a limit point c of A, lim⁡x→cf(x)=L holds if and only if f(xk)→L for every sequence (xk) with xk∈A, xk≠c for every k, and xk→c. The direction from the limit to sequences is a theorem of ZF; the converse uses the axiom of countable choice exactly once (Heine criterion: lim⁡x→cf(x)=L iff f(xk)→L for every sequence in A∖{c} converging to c, The Axiom of Countable Choice (ACω)).

[L5]

Convergence of a real sequence: xk→x when for every rational ε>0 there is K with ∣xk−x∣<ε for all k≥K; below every positive real lies a positive rational, so the test may equally be run at every real ε>0 (Limits and Cauchy sequences of reals, Sequences of reals: bounded, eventually, frequently, tails, subsequences, The rationals embed densely in the reals).

[L6]

Absolute value: ∣u∣≥0, and ∣u∣=0 exactly when u=0 (Basic properties of the absolute value).

Proof

technique · direct
1.1

The isolated case, both statements at once. Suppose c is an isolated point of A and fix a real η>0 with Nη(c)∩A={c}. Then statement 1 holds by [L3]. Statement 2 also holds: if xk∈A for every k and xk→c, then by [L5] there is K with ∣xk−c∣<η for all k≥K, so xk∈Nη(c)∩A={c} and hence xk=c and f(xk)=f(c) for all k≥K; a sequence eventually equal to f(c) converges to f(c), since ∣f(xk)−f(c)∣=0<ε for k≥K. So 1 and 2 are both true, and in particular equivalent.

L2L3L5L6
1.2

The limit-point case, from 1 to 2. Suppose c is a limit point of A and that f is continuous at c. Let (xk) satisfy xk∈A for every k and xk→c, and let a rational ε>0 be given. By [L1] fix a real δ>0 with ∣f(x)−f(c)∣<ε for every x∈A satisfying ∣x−c∣<δ; by [L5] fix K with ∣xk−c∣<δ for all k≥K. Every such k has xk∈A and ∣xk−c∣<δ, hence ∣f(xk)−f(c)∣<ε. As the rational ε>0 was arbitrary, f(xk)→f(c). Nothing was selected, so this is a theorem of ZF.

L1L5
1.3

The limit-point case, from 2 to 1. Suppose c is a limit point of A and that statement 2 holds. Every sequence (xk) with xk∈A, xk≠c for every k, and xk→c is in particular a sequence in A converging to c, so statement 2 gives f(xk)→f(c). That is the right-hand side of [L4] with L:=f(c), so [L4] yields that the limit of f at c exists and equals f(c), and [L3] turns that into continuity of f at c. This is the direction that inherits the single use of countable choice made in [L4].

L3L4
2.1

By [L2] the point c is either isolated in A or a limit point of A. In the first case step 1.1 proves both statements outright; in the second, step 1.2 gives 1 implies 2 and step 1.3 gives 2 implies 1. So statements 1 and 2 are equivalent, with the first implication free of choice and the second inheriting exactly one application of countable choice.

step 1.1step 1.2step 1.3L2∎

Remarks

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function

Statement

Let A⊆R, let f,g:A→R, let α∈R and let c∈A. Suppose f and g are continuous at c (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point). Then:

  1. f+g, αf and fg are continuous at c;
  2. ∣f∣, the function x↦∣f(x)∣, is continuous at c;
  3. max⁡{f,g} and min⁡{f,g}, defined pointwise by x↦max⁡{f(x),g(x)} and x↦min⁡{f(x),g(x)} (Maximum and minimum of a set), are continuous at c;
  4. if g(c)≠0 then, writing A0:={ x∈A:g(x)≠0 }, the point c lies in A0 and the quotient (f/g)∣A0:A0→R, x↦f(x)/g(x), is continuous at c as a function on A0.

Moreover, with no hypothesis at all:

  1. every constant function A→R and the identity id:A→R, x↦x, are continuous on A; hence so is x↦xn for every n∈N (Integer powers am), and hence so is every polynomial function x↦a0+a1x+⋯+anxn with real coefficients.

Consequently, if f and g are continuous on A then so are f+g, αf, fg, ∣f∣, max⁡{f,g} and min⁡{f,g}, and (f/g)∣A0 is continuous on A0.

Claim 4 is stated on A0 because f/g is not defined where g vanishes, and g may well vanish at points of A far from c. The hypothesis is g(c)≠0, not "g nowhere zero"; what it buys is that c itself lies in the smaller domain, which is what makes continuity there mean anything.

Nothing here is proved through a sequence. Claims 1 and 4 are read off from Sums, scalar multiples, products and quotients of function limits, the quotient under the hypothesis that the denominator limit is nonzero, which is itself proved from ε and δ, and claims 2, 3 and 5 are proved directly below. So no choice principle is used anywhere in this item.

Facts & Assumptions

Given: A set A⊆R, functions f,g:A→R, a real α, a point c∈A at which f and g are continuous, and, for claim 4, the hypothesis g(c)≠0 together with A0:={ x∈A:g(x)≠0 }.

[L1]

Continuity at c: for every real ε>0 there is a real δ>0 such that every x∈A with ∣x−c∣<δ satisfies ∣f(x)−f(c)∣<ε (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

[L3]

Algebra of function limits at a limit point c of A: if the limits of f and g at c exist with values L and M, then the limits of f+g, αf and fg at c exist with values L+M, αL and LM; and if M≠0 then c is a limit point of A0, and the limit of (f/g)∣A0 at c exists and equals L/M (Sums, scalar multiples, products and quotients of function limits, the quotient under the hypothesis that the denominator limit is nonzero).

[L4]

Sign preservation: if the limit of g at a limit point c of A exists and is nonzero, then c is a limit point of A0={ x∈A:g(x)≠0 } (If lim⁡x→cf(x)=L≠0 then ∣f∣>∣L∣/2 on a punctured neighbourhood of c; in particular if L>0 then f>L/2>0 there).

[L5]

Reverse triangle inequality: ∣∣u∣−∣v∣∣≤∣u−v∣ (The reverse triangle inequality); and ∣u∣≥0, ∣u∣=0 exactly when u=0, ∣uv∣=∣u∣∣v∣ (Basic properties of the absolute value).

[L6]

Maximum and minimum of a two-element set of reals exist (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set), and for all reals u,v one has max⁡{u,v}=12(u+v+∣u−v∣) and min⁡{u,v}=12(u+v−∣u−v∣).

[L7]

Ordered-field arithmetic in R: trichotomy and totality of the order, the field identities, and 0<1 so that 2≠0 and t/2 is defined (Ordered field, Field).

[L8]

Integer powers: a0=1 and an+1=an⋅a (Integer powers am).

Proof

technique · direct
1.1

Justification of the identity in [L6]. Let u,v∈R. By totality either u≥v or v≥u. If u≥v then u−v≥0, so ∣u−v∣=u−v and 12(u+v+∣u−v∣)=12(2u)=u=max⁡{u,v}, while 12(u+v−∣u−v∣)=v=min⁡{u,v}. If v≥u the same computation with the roles exchanged applies, since ∣u−v∣=v−u there.

L5L6L7
1.2

The isolated case. Suppose c is an isolated point of A, say Nη(c)∩A={c} with η>0 real. Then every function on A is continuous at c by [L2], which gives claims 1, 2 and 3 at once. For claim 4, assume g(c)≠0; then c∈A0, and Nη(c)∩A0⊆Nη(c)∩A={c} with c in the left-hand side, so c is an isolated point of A0 and every function on A0, in particular (f/g)∣A0, is continuous at c.

L2
1.3

Claim 2, at any point of A. Let a real ε>0 be given and let δ>0 be as in [L1] for f and this ε. For x∈A with ∣x−c∣<δ the reverse triangle inequality gives ∣∣f(x)∣−∣f(c)∣∣≤∣f(x)−f(c)∣<ε. So ∣f∣ is continuous at c, and no case distinction was needed.

L1L5
1.4

Claim 5, constants and the identity. If f is constant then ∣f(x)−f(c)∣=0<ε for every x∈A and every real ε>0, so any δ>0 serves. For the identity, given a real ε>0 take δ:=ε: every x∈A with ∣x−c∣<δ has ∣id(x)−id(c)∣=∣x−c∣<ε. Both are continuous at every point of A.

L1L5L7
1.5

The limit-point case, claim 1. Suppose c is a limit point of A. By [L2] the limits of f and of g at c exist and equal f(c) and g(c). By [L3] the limits of f+g, αf and fg at c exist and equal f(c)+g(c), αf(c) and f(c)g(c), which are exactly the values of those three functions at c; by [L2] again, each of them is continuous at c.

L2L3
1.6

The limit-point case, claim 4. Suppose c is a limit point of A and g(c)≠0. Then c∈A0, and by [L4] the point c is a limit point of A0. By [L3] the limit of (f/g)∣A0 at c exists and equals f(c)/g(c), which is the value of (f/g)∣A0 at c; by [L2] applied on the domain A0, that function is continuous at c.

L2L3L4
2.1

Claims 1 and 4 in general. By [L2] the point c is either isolated in A or a limit point of A; step 1.2 settles the first case and steps 1.5 and 1.6 the second. So claims 1 and 4 hold as stated.

step 1.2step 1.5step 1.6L2
3.1

Claim 3. By claim 1 the function f−g=f+(−1)g is continuous at c, by step 1.3 so is ∣f−g∣, and by claim 1 again so are f+g+∣f−g∣ and its scalar multiple by 1/2. By step 1.1 that scalar multiple is the function x↦max⁡{f(x),g(x)}, so the maximum is continuous at c; the same argument with −∣f−g∣ gives the minimum.

step 1.1step 1.3step 2.1L6L7
3.2

Claim 5, powers and polynomials. The map x↦x0 is the constant 1 and x↦x1 is the identity, both continuous on A by step 1.4; and if x↦xn is continuous on A then so is x↦xn+1=xn⋅x, being a product of two functions continuous on A by step 2.1. By induction on n, x↦xn is continuous on A for every n∈N. A polynomial function a0+a1x+⋯+anxn is obtained from these by finitely many scalar multiplications and additions, each of which preserves continuity by step 2.1.

step 1.4step 2.1L8
4.1

Claims 1 to 5 are proved, all of them at an arbitrary point c of A and therefore, applied at every point, on the whole of A; and no sequence and no choice principle was used.

step 1.3step 2.1step 3.1step 3.2∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passverified 2026-08-09 (gpt-5.6-terra-codex-subscription)Open item page →

A composite of continuous functions is continuous, with no side hypothesis of the kind the composition of limits needs

Statement

Let A,B⊆R, let g:A→R with g(A)⊆B, and let f:B→R, so that the composite f∘g:A→R is defined. Let c∈A. If g is continuous at c and f is continuous at g(c)∈B, then f∘g is continuous at c (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

Consequently, if g is continuous on A and f is continuous on B, then f∘g is continuous on A.

No side hypothesis is needed, and that is the whole point. The composition theorem for limits, Composition of limits holds under either hypothesis: f is defined at L with value M, or g avoids L on a punctured neighbourhood of c, must assume one of two extra conditions: either L∈B with f(L)=M, or g≠L on a punctured neighbourhood of c; with both dropped the statement is false, which is FALSE: lim⁡x→cf(g(x))=M whenever lim⁡x→cg=L and lim⁡y→Lf=M. The first of those conditions is exactly continuity of f at L written out, so under the hypotheses above it holds automatically and nothing has to be assumed. The mechanism is visible in the proof: Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point quantifies over ∣y−b∣<ρ rather than over 0<∣y−b∣<ρ, so the value y=b that the limit version cannot control is precisely the one the continuity hypothesis does control.

Facts & Assumptions

Given: Sets A,B⊆R, functions g:A→R with g(A)⊆B and f:B→R, a point c∈A at which g is continuous, and the hypothesis that f is continuous at b:=g(c)∈B.

[L1]

Continuity of g at c: for every real ρ>0 there is a real δ>0 such that every x∈A with ∣x−c∣<δ satisfies ∣g(x)−g(c)∣<ρ (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

[L2]

Continuity of f at b: for every real ε>0 there is a real ρ>0 such that every y∈B with ∣y−b∣<ρ satisfies ∣f(y)−f(b)∣<ε (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

Proof

technique · direct
1.1

Write b:=g(c); by hypothesis b∈B, since g(A)⊆B and c∈A. Also (f∘g)(c)=f(b).

given
1.2

Let a real ε>0 be given. By [L2] fix a real ρ>0 such that every y∈B with ∣y−b∣<ρ satisfies ∣f(y)−f(b)∣<ε.

L2choose
2.1

By [L1], applied with this ρ, fix a real δ>0 such that every x∈A with ∣x−c∣<δ satisfies ∣g(x)−b∣<ρ.

step 1.2L1choose
3.1

Let x∈A with ∣x−c∣<δ. Then g(x)∈B and ∣g(x)−b∣<ρ by step 2.1, so y:=g(x) is admissible in step 1.2 and gives ∣f(g(x))−f(b)∣<ε, that is ∣(f∘g)(x)−(f∘g)(c)∣<ε. Note that the case g(x)=b is included, by [L3].

step 1.1step 1.2step 2.1L3
4.1

The real ε>0 was arbitrary and a δ>0 was produced for it, so f∘g is continuous at c; applying this at every point of A gives continuity of f∘g on A whenever g is continuous on A and f on B.

step 3.1L1L2∎

Remarks

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

f:A→R is continuous on A if and only if the preimage of every open subset of R is the intersection with A of an open subset of R, and dually for closed sets

Statement

Let A⊆R and f:A→R. Call a set S⊆A relatively open in A when S=U∩A for some open U⊆R, and relatively closed in A when S=G∩A for some closed G⊆R (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen). For V⊆R write f−1(V):={ x∈A:f(x)∈V }. Then the following are equivalent.

  1. f is continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).
  2. f−1(V) is relatively open in A for every open V⊆R.
  3. f−1(F) is relatively closed in A for every closed F⊆R.

"Relatively open" is defined here inline, and on purpose. At this point in the reading order this library has no subspace-topology item for R, and the metric one (Isometry, isometric embedding, and the subspace metric on a subset) may not be reached before Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace has said that the two vocabularies agree, which is later on this page. The phrase above is therefore an abbreviation for the displayed condition and nothing more.

The preimage is taken inside A. f−1(V) is a subset of A, never of R, so claim 2 does not say that preimages of open sets are open. They are open only when A is itself open: then U∩A is an intersection of two open sets, hence open (Arbitrary unions and finite intersections of open subsets of R are open, and dually for closed sets). For A=[0,1] and f the identity, f−1((−1,1/2))=[0,1/2) is not open, and it is the trace on A of the open set (−1,1/2).

No choice principle is used. The open set witnessing claim 2 is not selected point by point; it is constructed as a single union over a family cut out by a property, which is the device the proof below makes explicit.

Facts & Assumptions

Given: A set A⊆R and a function f:A→R; for V⊆R, f−1(V)={ x∈A:f(x)∈V }.

[L1]

Continuity of f at c∈A: for every real ε>0 there is a real δ>0 with ∣f(x)−f(c)∣<ε for every x∈A satisfying ∣x−c∣<δ; equivalently f(A∩Nδ(c))⊆Nε(f(c)) (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L2]

Open sets of R: U is open when every x∈U has some Nε(x)⊆U; every neighbourhood Nε(x) is itself open; a set is closed exactly when its complement is open (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L4]

Set algebra: for V⊆R one has f−1(R∖V)=A∖f−1(V); and for U⊆R, A∖(U∩A)=(R∖U)∩A.

Proof

technique · direct
1.1

From 1 to 2: the canonical witness. Assume f is continuous on A and let V⊆R be open. Define U  :=  ⋃{ Nδ(x) : x∈f−1(V), δ∈R, δ>0, f(A∩Nδ(x))⊆V }. The family being united is cut out by a property of the pair (x,δ), so it is a set and nothing is selected from it. Each of its members is open by [L2], so U is open by [L3].

L2L3
1.2

f−1(V)⊆U∩A. Let x∈f−1(V), so x∈A and f(x)∈V. Since V is open, [L2] gives a real ε>0 with Nε(f(x))⊆V, and continuity at x gives, by [L1], a real δ>0 with f(A∩Nδ(x))⊆Nε(f(x))⊆V. So this pair (x,δ) contributes Nδ(x) to the union, and x∈Nδ(x) by [L2]. Hence x∈U, and x∈A.

L1L2
1.3

From 2 to 1. Assume claim 2, let c∈A and let a real ε>0 be given. The set V:=Nε(f(c)) is open by [L2], so f−1(V)=U∩A for some open U⊆R. Since ∣f(c)−f(c)∣=0<ε we have c∈f−1(V), hence c∈U, and [L2] gives a real δ>0 with Nδ(c)⊆U. Every x∈A with ∣x−c∣<δ then lies in U∩A=f−1(V), so f(x)∈Nε(f(c)), that is ∣f(x)−f(c)∣<ε. As c and ε were arbitrary, f is continuous on A.

L1L2
2.1

U∩A⊆f−1(V). Let y∈U∩A. Then y∈Nδ(x) for some pair (x,δ) occurring in the union, so y∈A∩Nδ(x) and therefore f(y)∈V by the defining property of that pair. Hence y∈f−1(V).

step 1.1
3.1

Claim 2 holds. By steps 1.2 and 2.1, f−1(V)=U∩A with U open, so f−1(V) is relatively open in A; and V was an arbitrary open subset of R.

step 1.1step 1.2step 2.1
4.1

2 and 3 are equivalent. Let F⊆R be closed and put V:=R∖F, which is open by [L2]. If claim 2 holds then f−1(V)=U∩A with U open, and by [L4] f−1(F)=A∖f−1(V)=A∖(U∩A)=(R∖U)∩A, with R∖U closed by [L2]; so f−1(F) is relatively closed. The converse runs the same computation in the other direction, starting from an open V, putting F:=R∖V and using f−1(V)=A∖f−1(F).

step 3.1L2L4
5.1

Statements 1, 2 and 3 are therefore equivalent, and the passage from 1 to 2 selected nothing.

step 3.1step 1.3step 4.1∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passverified 2026-08-09 (gpt-5.6-terra-codex-subscription)Open item page →

The image of a compact subset of R under a continuous real function is compact

Statement

Let A⊆R, let f:A→R be continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point) and let K⊆A be compact in the sense of Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset, that is, every family of open subsets of R whose union contains K has a finite subfamily whose union contains K. Then the image

f[K]  :=  { f(x):x∈K }

is a compact subset of R.

This theorem is stated twice in this library, on purpose. Its metric-space twin is The image of a compact metric space under a continuous map is compact, and so is the image of any compact subset, proved from the cover machinery of metric spaces; the proof below is R-native and uses only open subsets of R and the definition of continuity of this page. The duplication is deliberate and is acknowledged in exactly one place, Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace later on this page, which proves that the two notions of "compact subset of R" and the two notions of "continuous" coincide, so that the two theorems really are the same statement in two vocabularies.

No choice principle is used. The covering family built below is cut out by a property rather than selected point by point, and the only selection made is from a finite list, which needs no axiom.

Facts & Assumptions

Given: A set A⊆R, a function f:A→R continuous on A, and a compact set K⊆A; f[K]={ f(x):x∈K }.

[L1]

Continuity of f at x∈A: for every real ε>0 there is a real δ>0 with ∣f(y)−f(x)∣<ε for every y∈A satisfying ∣y−x∣<δ; equivalently f(A∩Nδ(x))⊆Nε(f(x)) (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L2]

Open sets: V⊆R is open when every point of V has a neighbourhood inside V, and every neighbourhood Nδ(x) is itself an open set containing x (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L3]

Compactness of K: for every family W of open subsets of R with K⊆⋃W, either K=∅ and the empty subfamily covers it, or there are n∈N and W0,…,Wn∈W with K⊆W0∪⋯∪Wn (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset).

Proof

technique · direct
1.1

If K=∅, then f[K]=∅, which is compact by [L3]. Hence suppose K≠∅ for the rest of the proof.

L3cases
1.2

Let V be a family of open subsets of R with f[K]⊆⋃V. Define W  :=  { Nδ(x) : x∈K, δ∈R, δ>0, and f(K∩Nδ(x))⊆V for some V∈V }. This family is cut out by a property of the pair (x,δ), so it is a set and nothing is selected in forming it; every member is an open subset of R by [L2].

L2
2.1

W covers K. Let x∈K. Then x∈A and f(x)∈f[K]⊆⋃V, so f(x)∈V for some V∈V. As V is open, [L2] gives a real ε>0 with Nε(f(x))⊆V, and [L1] gives a real δ>0 with f(A∩Nδ(x))⊆Nε(f(x))⊆V. Since K⊆A we get f(K∩Nδ(x))⊆V, so Nδ(x)∈W, and x∈Nδ(x) by [L2]. Hence K⊆⋃W.

step 1.2L1L2
3.1

By [L3] there are n∈N and members W0,…,Wn of W with K⊆W0∪⋯∪Wn. For each i≤n the membership Wi∈W asserts the existence of some V∈V with f(K∩Wi)⊆V; naming one such Vi for each of the finitely many indices i≤n requires no choice principle.

step 1.1step 1.2step 2.1L3choose
4.1

The finite subfamily works. Let z∈f[K], say z=f(x) with x∈K. By step 3.1 there is i≤n with x∈Wi, hence x∈K∩Wi and z=f(x)∈Vi. Therefore f[K]⊆V0∪⋯∪Vn, a union of finitely many members of V.

step 3.1
5.1

Every family of open subsets of R covering f[K] thus has a finite subfamily covering f[K], so f[K] is compact.

step 1.1step 1.2step 4.1L3∎

Remarks

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

A continuous real function on a compact subset of R is bounded

Statement

Let A⊆R, let f:A→R be continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point) and let K⊆A be compact (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset). Then f is bounded on K: there is a real M≥0 with

∣f(x)∣≤Mfor every x∈K.

Equivalently, f[K] is a bounded subset of R (Lower bound, bounded below, bounded set).

The hypothesis is compactness of K, not of A, and it cannot be relaxed to boundedness of K or to closedness of K alone: the identity is unbounded on the closed set [0,∞), and x↦1/x is unbounded on the bounded set (0,1). The general statement of that is Rudin 4.20, the sharp converse: on a noncompact E⊆R there is an unbounded continuous function and a bounded continuous function with no greatest value, and if E is bounded there is a continuous function on E that is not uniformly continuous, later on this page.

Facts & Assumptions

Given: A set A⊆R, a function f:A→R continuous on A, and a compact set K⊆A.

[L2]

A subset of R is compact if and only if it is closed and bounded (A subset of R is compact if and only if it is closed and bounded).

[L3]

A set S⊆R is bounded when there are reals ℓ,u with ℓ≤s≤u for every s∈S (Lower bound, bounded below, bounded set).

[L4]

A nonempty finite set of reals has a maximum (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set), and the order of R is total (Ordered field).

[L5]

Absolute value: ∣u∣≥0; ∣u∣=u when u≥0 and ∣u∣=−u when u≤0; and t≤∣t∣ for every real t (Basic properties of the absolute value).

Proof

technique · direct
1.1

By [L1] the set f[K] is compact, and by [L2] it is therefore closed and bounded.

L1L2
2.1

By [L3] fix reals ℓ and u with ℓ≤z≤u for every z∈f[K], and put M:=max⁡{ ∣ℓ∣, ∣u∣ }, which exists by [L4] and satisfies M≥0 by [L5].

step 1.1L3L4L5choose
3.1

Let x∈K and put z:=f(x)∈f[K], so ℓ≤z≤u. If z≥0 then ∣z∣=z≤u≤∣u∣≤M; if z<0 then ∣z∣=−z≤−ℓ≤∣ℓ∣≤M, using ℓ≤z and −ℓ≤∣−ℓ∣=∣ℓ∣. In both cases ∣f(x)∣≤M.

step 2.1L4L5
4.1

So ∣f(x)∣≤M for every x∈K, with M≥0 a real; equivalently f[K] is bounded, which is what step 1.1 already recorded.

step 2.1step 3.1L3∎

Remarks

  • Boundedness is the weak half of the extreme value theorem. What compactness gives in addition is that the two bounds are attained, which is Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value; the supremum of f[K] exists as soon as f[K] is nonempty and bounded above, and the work is entirely in showing that it belongs to f[K].

  • Boundedness of the domain is not what is used. The proof never looks at K after the first line: the whole content is that the image is compact, hence bounded. That is why the same one-line argument gives boundedness of a continuous function on any compact set, however complicated.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value

Statement

Let A⊆R, let f:A→R be continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point) and let K⊆A be nonempty and compact (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset). Then sup⁡f[K] and inf⁡f[K] exist and are attained: there are p,q∈K with

f(q)  =  inf⁡f[K]  ≤  f(x)  ≤  sup⁡f[K]  =  f(p)for every x∈K.

Equivalently, the set f[K] has a maximum and a minimum (Maximum and minimum of a set), namely max⁡f[K]=f(p) and min⁡f[K]=f(q).

Nonemptiness of K is a hypothesis, not an oversight. For K=∅ the set f[K] is empty, and neither a supremum nor a maximum of the empty set exists in this library (Complete ordered field (least-upper-bound property) supplies suprema of nonempty sets bounded above only).

This theorem is stated twice in this library, on purpose. Its metric-space twin is A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value, proved from the cover machinery of metric spaces; the proof below is R-native, running through Heine-Borel for R and the order-completeness of R, and it uses no cover argument beyond the one already spent in The image of a compact subset of R under a continuous real function is compact. That the two statements are the same statement in two vocabularies is proved in Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace, later on this page.

Facts & Assumptions

Given: A set A⊆R, a function f:A→R continuous on A, and a nonempty compact set K⊆A; write S:=f[K].

[L1]

S=f[K] is compact (The image of a compact subset of R under a continuous real function is compact), and it is nonempty because K is.

[L2]

S is bounded: there is a real M≥0 with ∣z∣≤M for every z∈S, so −M is a lower bound and M an upper bound of S (A continuous real function on a compact subset of R is bounded, Lower bound, bounded below, bounded set).

[L4]

Least upper bounds: a nonempty subset of R bounded above has a supremum (Complete ordered field (least-upper-bound property)); a nonempty subset bounded below has an infimum (Every nonempty set bounded below has an infimum, Greatest lower bound (infimum)).

[L5]

Epsilon characterisations: for nonempty S bounded above and u=sup⁡S, every real ε>0 admits s∈S with u−ε<s; dually for ℓ=inf⁡S there is s∈S with s<ℓ+ε (Epsilon characterisation of the supremum, Epsilon characterisation of the infimum).

[L7]

A maximum of a set is an element of it that bounds it above, and a minimum is an element that bounds it below (Maximum and minimum of a set).

Proof

technique · direct
1.1

By [L1] the set S=f[K] is nonempty and compact, and by [L2] it is bounded; by [L3] it is closed.

L1L2L3
2.1

By [L4] the supremum u:=sup⁡S and the infimum ℓ:=inf⁡S exist.

step 1.1L4
3.1

u is adherent to S. Let a real ε>0 be given. By [L5] there is s∈S with u−ε<s, and s≤u<u+ε since u bounds S above; hence ∣s−u∣<ε, that is s∈Nε(u)∩S. So every neighbourhood of u meets S.

step 2.1L5L6
3.2

ℓ is adherent to S. Symmetrically, [L5] gives s∈S with s<ℓ+ε, and ℓ≤s since ℓ bounds S below; hence s∈Nε(ℓ)∩S for every real ε>0.

step 2.1L5L6
4.1

By [L6] the two steps above say u∈S‾ and ℓ∈S‾; and S is closed by step 1.1, so S‾=S and therefore u∈S and ℓ∈S.

step 1.1step 3.1step 3.2L6
5.1

Since u∈S=f[K] there is p∈K with f(p)=u, and since ℓ∈S there is q∈K with f(q)=ℓ.

step 4.1choose
6.1

For every x∈K the value f(x) lies in S, so ℓ≤f(x)≤u, that is f(q)≤f(x)≤f(p). Hence u=sup⁡f[K]=f(p) is a maximum of f[K] and ℓ=inf⁡f[K]=f(q) is a minimum of it, both attained at points of K.

step 2.1step 4.1step 5.1L7∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

Intermediate value theorem, by bisection with a canonical left-half rule: a continuous function on [a,b] takes every value between f(a) and f(b)

Statement

Let a,b∈R with a≤b, let f:[a,b]→R be continuous on the closed bounded interval [a,b] (Intervals of R: the nine order-convex forms, nondegeneracy, and length, Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point), and let y∈R satisfy

f(a)≤y≤f(b)orf(b)≤y≤f(a).

Then there is c∈[a,b] with f(c)=y.

The construction is canonical, so no choice principle is used. The bisection below tests the left half first and takes the right half only when the left one has been ruled out, so the passage from one interval to the next is a function of that interval, and The recursion theorem applies with nothing selected. This is the same discipline the library uses wherever a sequence is built one term at a time.

Completeness of R is what does the work. The bisection produces a nested sequence of closed bounded intervals whose lengths tend to 0, and it is A nested sequence of nonempty closed bounded intervals has nonempty intersection, and the intersection is a single point exactly when the lengths tend to 0 — hence the least-upper-bound property — that supplies the point. Over an ordered field that is not complete the theorem fails; the witness for that, stated for an arbitrary ordered field and worked over Q, is On a closed interval of Q there is a continuous unbounded function, a bounded one with no maximum, and one without the intermediate value property, which states its own ε-δ continuity inline and is not an instance of this page's definition.

Facts & Assumptions

Given: Reals a≤b, a function f:[a,b]→R continuous on [a,b], and a real y with f(a)≤y≤f(b) or f(b)≤y≤f(a).

[L2]

Recursion: for a set X, an element x0∈X and a function F:X→X there is a unique g:N→X with g(0)=x0 and g(k+1)=F(g(k)) for every k (The recursion theorem).

[L3]

Nested intervals: if Ik=[ak,bk] with ak≤bk and Ik+1⊆Ik for every k∈N, then ⋂kIk is nonempty, and it is a single point exactly when the lengths bk−ak tend to 0 (A nested sequence of nonempty closed bounded intervals has nonempty intersection, and the intersection is a single point exactly when the lengths tend to 0, Intervals of R: the nine order-convex forms, nondegeneracy, and length, Limits and Cauchy sequences of reals).

[L5]

Powers: (2−1)k=(2k)−1 for every k∈N (Laws of integer exponents, Integer powers am).

[L7]

Limits preserve non-strict inequalities (Limits preserve non-strict inequalities).

[L8]

Order and field arithmetic in R: trichotomy and totality, so exactly one of f(m)≥y and f(m)<y holds; halving and the ordered-field identities (Ordered field, Complete ordered field (least-upper-bound property)); and ∣t∣≤s whenever −s≤t≤s (Basic properties of the absolute value).

Proof

technique · constructive
1.1

Reduction. It is enough to prove the theorem under the hypothesis f(a)≤y≤f(b). Indeed, in the remaining case f(b)≤y≤f(a), put h:=(−1)f and z:=−y; then h is continuous on [a,b] by [L1] and h(a)=−f(a)≤−y=z≤−f(b)=h(b), so a point c∈[a,b] with h(c)=z is a point with f(c)=y.

L1L8suffices: assume f(a) le y le f(b)
1.2

The bisection map. Assume f(a)≤y≤f(b) and put X  :=  { (u,v)∈R×R : a≤u≤v≤b, f(u)≤y≤f(v) }, so (a,b)∈X. For (u,v)∈X write m:=(u+v)/2, which satisfies a≤u≤m≤v≤b and so lies in [a,b], and define F(u,v)  :=  {(u, m)if f(m)≥y,(m, v)if f(m)<y. By trichotomy exactly one clause applies, so F is a function on X; and F(u,v)∈X in both clauses, since in the first f(u)≤y≤f(m) and in the second f(m)≤y≤f(v). The left half is tested first and the right half is taken only when the left is excluded, so nothing is selected.

L8construct
2.1

The nested sequence. By [L2] applied to X, the element (a,b) and the map F, there is a unique g:N→X with g(0)=(a,b) and g(k+1)=F(g(k)). Write g(k)=(ak,bk) and Ik:=[ak,bk]. Then for every k: a≤ak≤bk≤b and f(ak)≤y≤f(bk), because g(k)∈X; and Ik+1⊆Ik, since in either clause of the definition of F the new endpoints lie in [ak,bk] and the new interval is [ak,mk] or [mk,bk] with mk=(ak+bk)/2.

step 1.2L2L8
3.1

The lengths. In both clauses the new length is mk−ak=(bk−ak)/2 or bk−mk=(bk−ak)/2, so bk+1−ak+1=(bk−ak)/2; with b0−a0=b−a an induction on k gives bk−ak=(b−a) (2−1)k for every k∈N, that is (b−a)/2k by [L5]. Since ∣2−1∣<1, [L4] gives (2−1)k→0 and hence bk−ak→0.

step 2.1L4L5L8
4.1

The point. By [L3] applied to the nested family (Ik), whose lengths tend to 0 by step 3.1, the intersection ⋂kIk is a single point; call it c. Then c∈I0=[a,b] and ak≤c≤bk for every k.

step 2.1step 3.1L3construct
5.1

The endpoints converge to c. Let a rational ε>0 be given. By step 3.1 there is K with bk−ak<ε for all k≥K. For such k, from ak≤c≤bk we get −(bk−ak)≤ak−c≤0 and 0≤bk−c≤bk−ak, so ∣ak−c∣≤bk−ak<ε and ∣bk−c∣≤bk−ak<ε by [L8]. Hence ak→c and bk→c.

step 3.1step 4.1L8
6.1

Passing to the limit. The point c lies in [a,b], so f is continuous at c, and [L6] applied to the two sequences of step 5.1 gives f(ak)→f(c) and f(bk)→f(c).

step 4.1step 5.1L6
7.1

By step 2.1, f(ak)≤y for every k; the constant sequence with value y converges to y by [L4], so [L7] gives f(c)≤y. Likewise y≤f(bk) for every k gives y≤f(c). Hence f(c)=y.

step 2.1step 6.1L4L7L8
8.1

A point c∈[a,b] with f(c)=y has therefore been constructed, under the reduction of step 1.1 and hence in both cases of the hypothesis.

step 1.1step 4.1step 7.1discharge-construct: c is the unique point of the nested intersection∎

Remarks

  • Why the left half is tested first. The bisection has to choose one of two halves at every stage, and if the rule were "choose a half in which the sign change persists" the construction would be a dependent choice, not a recursion. Testing f(m)≥y and taking the left half in that case makes the successor a function of its predecessor, so The recursion theorem applies verbatim. The same device is used in Every nonempty perfect subset of R is uncountable and in the bisection proof of Heine-Borel.

  • What the theorem does not say. It does not say that c is unique, and it does not say that the set of solutions is an interval; f may take the value y on a complicated set. It also does not say that a function with the intermediate value property is continuous — that converse is false, and the witness for it needs machinery that is not available at this point in the reading order.

  • Only the choice-free direction of the sequential criterion is used. Step 6.1 turns a convergent sequence into a convergent image sequence, which is the implication proved in ZF (f is continuous at c∈A if and only if f(xk)→f(c) for every sequence in A converging to c, the converse direction costing countable choice); the converse, which spends countable choice, is never invoked here.

CorollaryStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

The image of an interval under a continuous real function is order-convex, hence an interval, and the image of a closed bounded interval is a closed bounded interval

Statement

Let A⊆R, let f:A→R be continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point) and let I⊆A be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length). Then:

  1. f[I] is order-convex, hence connected (A subset of R is connected if and only if it is order-convex, that is, an interval, Separated sets, disconnection, and connected subset of R);
  2. if I=[a,b] with a≤b, then f[I]=[m,M] where m=min⁡f[I] and M=max⁡f[I] (Maximum and minimum of a set) — a closed bounded interval, degenerate exactly when f is constant on [a,b].

"Interval" means "order-convex" here. As A subset of R is connected if and only if it is order-convex, that is, an interval records, this library proves that the connected subsets of R are exactly the order-convex ones, and does not prove that every order-convex subset is one of the nine written forms of Intervals of R: the nine order-convex forms, nondegeneracy, and length. Claim 1 is therefore stated as order-convexity, which is what the intermediate value theorem delivers; claim 2 identifies the written form in the one case where the extreme value theorem supplies the endpoints.

Facts & Assumptions

Given: A set A⊆R, a function f:A→R continuous on A, and an order-convex set I⊆A.

[L1]

Intermediate value theorem: if u≤v in R, if f is continuous on [u,v] and if w lies between f(u) and f(v) in either order, then f(t)=w for some t∈[u,v] (Intermediate value theorem, by bisection with a canonical left-half rule: a continuous function on [a,b] takes every value between f(a) and f(b)).

[L2]

Continuity passes to subsets of the domain: if B⊆A then f∣B is continuous on B, since the defining condition quantifies over fewer points (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

[L3]

Order-convexity: x,z∈S and x≤w≤z imply w∈S; every closed bounded interval [u,v] with u≤v is order-convex and is a subset of any order-convex set containing u and v (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L6]

Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value on it (Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value, Maximum and minimum of a set).

Proof

technique · direct
1.1

Claim 1. Let u′,v′∈f[I] and let w satisfy u′≤w≤v′. Write u′=f(p) and v′=f(q) with p,q∈I, and let [s,t] be the closed bounded interval with {s,t}={p,q} and s≤t; by [L3] and order-convexity of I we have [s,t]⊆I⊆A.

L3choose
1.2

Claim 2, the endpoints. Suppose I=[a,b] with a≤b. By [L5] the set [a,b] is nonempty and compact, so by [L6] there are q,p∈[a,b] with f(q)≤f(x)≤f(p) for every x∈[a,b]; put m:=f(q) and M:=f(p), so m=min⁡f[I] and M=max⁡f[I] and m≤M.

L5L6choose
2.1

By [L2] the restriction of f to [s,t] is continuous on [s,t], and w lies between f(s) and f(t) in one order or the other, since {f(s),f(t)}={u′,v′} and u′≤w≤v′. By [L1] there is c∈[s,t]⊆I with f(c)=w, so w∈f[I].

step 1.1L1L2
3.1

So f[I] is order-convex, and by [L4] it is connected. This is claim 1.

step 2.1L4
4.1

Claim 2, the two inclusions. Every z∈f[I] satisfies m≤z≤M by step 1.2, so f[I]⊆[m,M]. Conversely, m and M lie in f[I] and f[I] is order-convex by step 3.1, so every w with m≤w≤M lies in f[I]; hence [m,M]⊆f[I]. Therefore f[I]=[m,M], a closed bounded interval, and it is the single point {m} exactly when m=M, that is exactly when f is constant on [a,b].

step 3.1step 1.2L3∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

Every continuous map of a closed bounded interval into itself has a fixed point

Statement

Let a,b∈R with a≤b and let φ:[a,b]→R be continuous on [a,b] (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point, Intervals of R: the nine order-convex forms, nondegeneracy, and length) with

φ(x)∈[a,b]for every x∈[a,b].

Then φ has a fixed point: there is c∈[a,b] with φ(c)=c.

This is the one-dimensional case of Brouwer's theorem, and here it is elementary. The whole content is that φ(x)−x is ≥0 at the left endpoint and ≤0 at the right, so the intermediate value theorem produces a zero. Nothing about contraction, and no metric hypothesis, is needed: the map is not assumed to shrink distances, and the fixed point need not be unique.

Both hypotheses on the interval are used. The interval must be closed, or the fixed point can escape through an endpoint; and it must be bounded, or there need be no fixed point at all, as x↦x+1 on [0,∞) shows.

Facts & Assumptions

Given: Reals a≤b and a continuous φ:[a,b]→R with φ(x)∈[a,b] for every x∈[a,b].

[L2]

Intermediate value theorem: if g is continuous on [a,b] with a≤b and y lies between g(a) and g(b) in either order, then g(c)=y for some c∈[a,b] (Intermediate value theorem, by bisection with a canonical left-half rule: a continuous function on [a,b] takes every value between f(a) and f(b)).

[L3]

Membership in [a,b] means a≤x≤b (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L4]

Ordered-field arithmetic in R: adding and subtracting preserves order, and u−v≥0 exactly when u≥v (Ordered field, Complete ordered field (least-upper-bound property)).

Proof

technique · direct
1.1

Define g:[a,b]→R by g(x):=φ(x)−x. By [L1] the function g is continuous on [a,b], being the sum of φ and (−1) times the identity.

L1
1.2

By hypothesis φ(a)∈[a,b], so φ(a)≥a and hence g(a)=φ(a)−a≥0 by [L4]. Likewise φ(b)∈[a,b] gives φ(b)≤b and hence g(b)=φ(b)−b≤0.

L3L4
2.1

So g(b)≤0≤g(a): the value 0 lies between g(b) and g(a). By [L2], applied to g on [a,b] with y:=0, there is c∈[a,b] with g(c)=0.

step 1.1step 1.2L2choose
3.1

Then φ(c)−c=0, that is φ(c)=c, with c∈[a,b]: the map φ has a fixed point.

step 2.1L4∎

Remarks

  • Uniqueness is not claimed and is false in general. The identity map of [a,b] into itself is continuous and fixes every point. What forces uniqueness is a contraction hypothesis, which is the setting of the Banach fixed point theorem in a complete metric space; that theorem also produces the fixed point as a limit of iterates, whereas the argument above only asserts that one exists.

  • The interval may not be replaced by an arbitrary compact set. The map x↦−x carries the compact set {−1,1} into itself, is continuous, and fixes nothing. Order-convexity, not compactness alone, is what the intermediate value theorem needs.

  • A worked instance is A worked fixed point on [1,2] for the map x↦(x+2/x)/2, from the one-dimensional fixed point theorem ↗ on the companion page, where φ(x)=(x+2/x)/2 maps [1,2] into itself and its unique fixed point is 2.

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and let f:I→R satisfy

f(x)≤f(y)whenever x,y∈I and x≤y.

If the image f[I] is order-convex, then f is continuous on I (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

No definition of a monotone function is used, and none is available at this point in the reading order. The hypothesis is written out as the displayed inequality; the classification of monotone functions and their discontinuities comes later in the library. Equivalently, by A subset of R is connected if and only if it is order-convex, that is, an interval, the hypothesis on the image is that f[I] is connected (Separated sets, disconnection, and connected subset of R).

The hypothesis on the image cannot be dropped. Define f on I=[0,1] by f(x):=x for x<1 and f(1):=2. It satisfies the displayed inequality, its image is [0,1)∪{2}, which is not order-convex, and it is not continuous at 1: no δ works for ε=1/2, since points of [0,1) arbitrarily close to 1 have values close to 1, at distance close to 1 from f(1)=2.

This is a genuine converse to the intermediate value property, in the presence of the inequality. It does not need one-sided limits of monotone functions, which are not available at this point in the reading order; the entire proof is the two paragraphs below, which read the required δ off the image.

Facts & Assumptions

Given: An order-convex set I⊆R and a function f:I→R with f(x)≤f(y) whenever x,y∈I and x≤y, such that f[I] is order-convex; and a point c∈I together with a real ε>0.

[L1]

Continuity of f at c: for every real ε>0 there is a real δ>0 with ∣f(x)−f(c)∣<ε for every x∈I satisfying ∣x−c∣<δ (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L2]

Order-convexity of f[I]: if u,v∈f[I] and u≤w≤v then w∈f[I] (Intervals of R: the nine order-convex forms, nondegeneracy, and length); equivalently f[I] is connected (A subset of R is connected if and only if it is order-convex, that is, an interval, Separated sets, disconnection, and connected subset of R).

[L3]

Order and field arithmetic in R: trichotomy and totality of the order, so any two reals are comparable and exactly one of r<c, r=c, r>c holds; ε>0 gives ε/2>0 and f(c)−ε<f(c)−ε/2<f(c) (Ordered field).

[L4]

The minimum of a two-element set of reals exists and is one of the two elements (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set).

[L5]

Absolute value: for s>0, ∣t∣<s holds exactly when −s<t<s (Basic properties of the absolute value).

Proof

technique · direct
1.1

A point of I below c with a value close to f(c), when one exists at all. Suppose some p∈I has p<c. We claim there is q∈I with q<c and f(q)>f(c)−ε. If there were none, then f(q)≤f(c)−ε for every q∈I with q<c, and in particular f(p)≤f(c)−ε. Put w:=f(c)−ε/2, so f(p)≤f(c)−ε<w<f(c) by [L3]. Since f(p),f(c)∈f[I], [L2] gives r∈I with f(r)=w. By [L3] exactly one of r<c, r=c, r>c holds: the first gives w=f(r)≤f(c)−ε<w, the second gives w=f(c), and the third gives w=f(r)≥f(c) by the monotonicity hypothesis; each contradicts f(c)−ε<w<f(c). So the claimed q exists.

L2L3
2.1

The left radius. If some p∈I has p<c, fix q as in step 1.1 and put δ1:=c−q>0; then every x∈I with c−δ1<x≤c satisfies q<x≤c, hence f(q)≤f(x)≤f(c) by monotonicity, hence f(c)−ε<f(x)≤f(c). If no point of I lies below c, put δ1:=1; then the only x∈I with c−δ1<x≤c is x=c, for which f(c)−ε<f(c)=f(x)≤f(c) holds as well. In both cases δ1>0 and every x∈I with c−δ1<x≤c satisfies f(c)−ε<f(x)≤f(c).

step 1.1L3choose
2.2

The right radius, symmetrically. Suppose some p∈I has p>c. If every s∈I with s>c had f(s)≥f(c)+ε, then with w′:=f(c)+ε/2 we would have f(c)<w′<f(c)+ε≤f(p), so [L2] would give r∈I with f(r)=w′; but by [L3] exactly one of r>c, r=c, r<c holds, and the first gives w′=f(r)≥f(c)+ε>w′, the second gives w′=f(c), and the third gives w′=f(r)≤f(c) by the monotonicity hypothesis, each contradicting f(c)<w′<f(c)+ε. So there is s∈I with s>c and f(s)<f(c)+ε; put δ2:=s−c>0. If no point of I lies above c, put δ2:=1. In both cases δ2>0 and every x∈I with c≤x<c+δ2 satisfies f(c)≤f(x)<f(c)+ε.

step 1.1L2L3choose
3.1

Combining. Put δ:=min⁡{δ1,δ2}, which is a positive real by [L4]. Let x∈I with ∣x−c∣<δ, so c−δ<x<c+δ by [L5]. By totality either x≤c, and then c−δ1≤c−δ<x≤c, so step 2.1 gives f(c)−ε<f(x)≤f(c); or x≥c, and then c≤x<c+δ≤c+δ2, so step 2.2 gives f(c)≤f(x)<f(c)+ε. In either case −ε<f(x)−f(c)<ε, that is ∣f(x)−f(c)∣<ε by [L5].

step 2.1step 2.2L3L4L5
4.1

The point c∈I and the real ε>0 were arbitrary, so by [L1] the function f is continuous at every point of I, that is, continuous on I.

step 3.1L1∎

Remarks

  • Where order-convexity of the image is used, and where it is not. It is used exactly twice, in steps 1.1 and 2.2, each time to convert a value strictly between two attained values into an attained value. Nothing else in the argument looks at the image. In particular, no continuity of f is assumed anywhere, which is what makes the lemma a converse rather than a reformulation.

  • The endpoint cases are not a technicality. If c is the left endpoint of I there is no point of I below it, and the left half of the estimate is vacuous; the same at the right. Handling them by the fixed radius 1 keeps the proof free of any hypothesis that I be open or nondegenerate.

  • What this lemma is for. It is the standard route to continuity of a function defined by a monotone construction whose image is known independently — the Cantor function is the classical instance, its image being all of [0,1] — and it is stated here as a standalone lemma so that a later page may cite it rather than repeat the argument.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-07-27Open item page →

Uniform continuity of f:A→R: one δ serving every pair of points of A

Definition

Let A⊆R and let f:A→R. Then f is uniformly continuous on A when

(∀ε>0) (∃δ>0) (∀x,x′∈A) [ ∣x−x′∣<δ ⟹ ∣f(x)−f(x′)∣<ε ],

with ε and δ ranging over the positive reals.

The whole content is in the order of the quantifiers. Written out, continuity on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point) is

∀ε ∀c∈A ∃δ ∀x∈A,

and uniform continuity is

∀ε ∃δ ∀x′∈A ∀x∈A.

Moving ∃δ to the left of the point quantifier is the entire difference: for continuity the radius may shrink from point to point, for uniform continuity one radius must serve the whole of A at once. This is the same distinction, for the same reason, that Uniform continuity of a map of metric spaces: one δ serving every point draws for maps of metric spaces.

Uniform continuity implies continuity. Given ε>0, take the δ supplied by uniform continuity and, at a point c∈A, apply the condition with x′:=c: every x∈A with ∣x−c∣<δ satisfies ∣f(x)−f(c)∣<ε. So the same δ witnesses continuity at every point of A simultaneously. The converse fails, and the failure is not marginal: FALSE: every continuous real function is uniformly continuous on its domain refutes it on this page, and the companion page works two witnesses out in full.

Uniform continuity is a property of the pair (f,A), not of f alone. The same formula may be uniformly continuous on one set and not on another: x↦1/x is uniformly continuous on [1,∞) and not on (0,1), and x↦x2 is uniformly continuous on every bounded interval and not on R. Restricting the domain therefore never destroys uniform continuity, since the condition then quantifies over fewer pairs; enlarging it may.

The two points are unordered and may coincide. Nothing above excludes x=x′, at which the implication reads ∣f(x)−f(x)∣=0<ε (Basic properties of the absolute value) and is automatic, and the condition is symmetric in the two points because ∣x−x′∣=∣x′−x∣.

Remarks

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace

Statement

Let A⊆R carry the subspace metric of the usual metric dR(x,y)=∣x−y∣ of R, that is dA(x,y)=∣x−y∣ for x,y∈A (The absolute value makes R a metric space: d(x,y)=∣x−y∣ is a metric, its open balls are the intervals (x−r,x+r), and it is unbounded, Isometry, isometric embedding, and the subspace metric on a subset), and let f:A→R, regarded also as a map of metric spaces (A,dA)→(R,dR). Then the R-native notions of this page and the metric-space notions of the earlier pages are the same notions, in the following five senses.

  1. Continuity. For every c∈A: f is continuous at c in the sense of Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point if and only if f is continuous at c in the sense of Continuity of a map between metric spaces, at a point and globally, in the ε-δ form. Consequently f is continuous on A if and only if it is continuous as a map of metric spaces.
  2. Uniform continuity. f is uniformly continuous on A in the sense of Uniform continuity of f:A→R: one δ serving every pair of points of A if and only if it is uniformly continuous as a map of metric spaces (Uniform continuity of a map of metric spaces: one δ serving every point).
  3. Lipschitz. For a real L≥0: f is Lipschitz with constant L as a map of metric spaces (Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction) if and only if ∣f(x)−f(x′)∣≤L ∣x−x′∣for all x,x′∈A. This displayed condition is what "f is Lipschitz with constant L" means for a real function on A in this library; no second definition is made.
  4. Hölder. For a rational α with 0<α≤1 and a real C≥0: f is α-Hölder with constant C as a map of metric spaces if and only if ∣f(x)−f(x′)∣≤C ∣x−x′∣αfor all x,x′∈A, the power being the rational power of a nonnegative base (Rational powers ar of a positive base).
  5. Compactness, in both senses used in this library. For K⊆R with the subspace metric dK:

Two consequences are recorded, since they are the reason the dictionary is stated as a lemma rather than as a remark.

  1. The regularity hierarchy transfers verbatim. By clauses 1 to 4 and 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: a Lipschitz f:A→R is uniformly continuous on A; an α-Hölder f with rational 0<α≤1 is uniformly continuous on A; a uniformly continuous f is continuous on A; and if A is nonempty and bounded, a Lipschitz f is α-Hölder for every rational α with 0<α≤1. No strictness is claimed here, and none is claimed there.
  2. Cauchy sequences transfer. A sequence (xk) with terms in A is Cauchy in (A,dA) (Cauchy sequence in a metric space) if and only if it is Cauchy as a sequence of reals (Limits and Cauchy sequences of reals); so by clause 2 and A uniformly continuous map sends Cauchy sequences to Cauchy sequences, a uniformly continuous f:A→R carries Cauchy sequences of A to Cauchy sequences of R.

Why this lemma exists, and why it is a lemma. Three results of this page — The image of a compact subset of R under a continuous real function is compact, Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value and Heine-Cantor in R: a continuous real function on a compact subset of R is uniformly continuous — are stated a second time here, having already been proved metric-generally as The image of a compact metric space under a continuous map is compact, and so is the image of any compact subset, A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value and Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous. The duplication is deliberate: the R-native proofs run through A subset of R is compact if and only if it is closed and bounded and A subset of R is compact iff it is sequentially compact, which are order-based, while the metric proofs run through the cover machinery of metric spaces. This item is the single place in the library where that duplication is acknowledged, and clauses 1 and 5 are what make the two families of statements literally the same statements. It is a lemma, and not a remark, precisely so that later pages can cite it and move between the two vocabularies.

Clause 5 closes a second seam. The phrase compact subset of R is defined twice in this library — metrically, as compactness of the metric subspace (Open cover, subcover, compact metric space, and compact subset of a metric space), and R-natively, by covers by open subsets of R (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset) — and until this clause no item asserted that the two agree.

Facts & Assumptions

Given: A set A⊆R with the subspace metric dA(x,y)=∣x−y∣, a function f:A→R, and a set K⊆R with the subspace metric dK.

[L2]

Subspace metric: for S⊆R the restriction dS of dR to S×S is a metric on S, so dS(x,y)=∣x−y∣ for x,y∈S (Isometry, isometric embedding, and the subspace metric on a subset).

[L3]

Metric continuity at a∈X: for every real ε>0 there is a real δ>0 such that every x∈X with dX(x,a)<δ satisfies dY(f(x),f(a))<ε (Continuity of a map between metric spaces, at a point and globally, in the ε-δ form).

[L4]

Metric uniform continuity: for every real ε>0 there is a real δ>0 such that all x,x′∈X with dX(x,x′)<δ satisfy dY(f(x),f(x′))<ε (Uniform continuity of a map of metric spaces: one δ serving every point).

[L6]

Lipschitz and Hölder for a map of metric spaces: dY(f(x),f(x′))≤L dX(x,x′), respectively dY(f(x),f(x′))≤C dX(x,x′)α for a rational α with 0<α≤1, the power being that of Rational powers ar of a positive base with the convention 0α=0 (Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction).

[L7]

The regularity hierarchy for maps of metric spaces: Lipschitz implies uniformly continuous, uniformly continuous implies continuous, α-Hölder implies uniformly continuous, and on a nonempty bounded space Lipschitz implies α-Hölder for every rational α∈(0,1] (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).

[L8]

Intrinsic character of compactness: a subset K of a metric space X is a compact metric space in its own right, with the subspace metric, exactly when every family of open subsets of X whose union contains K has a finite subfamily whose union contains K (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, Open cover, subcover, compact metric space, and compact subset of a metric space).

[L9]
[L10]

Metric convergence: xk→p in (X,d) means d(xk,p)→0 in R (Convergence of a sequence in a metric space: xk→x iff d(xk,x)→0 in R); convergence and the Cauchy condition for real sequences are those of Limits and Cauchy sequences of reals and Sequences of reals: bounded, eventually, frequently, tails, subsequences; a metric is nonnegative (Nonnegativity of a metric is a consequence of the other axioms, not an axiom); and ∣u∣≥0 with ∣∣u∣∣=∣u∣ (Basic properties of the absolute value).

[L11]

Cauchy in a metric space: (xk) is Cauchy in (X,d) when for every rational ε>0 there is N with d(xm,xn)<ε for all m,n≥N (Cauchy sequence in a metric space).

[L12]

A uniformly continuous map of metric spaces sends Cauchy sequences to Cauchy sequences (A uniformly continuous map sends Cauchy sequences to Cauchy sequences).

Proof

technique · direct
1.1

The two distances are the two absolute values. By [L1] and [L2], for x,x′∈A we have dA(x,x′)=∣x−x′∣, and for u,v∈R we have dR(u,v)=∣u−v∣; in particular dR(f(x),f(x′))=∣f(x)−f(x′)∣.

L1L2
1.2

Clause 5, the cover half. Take the ambient metric space to be (R,dR) and K⊆R with dK. By [L8], (K,dK) is a compact metric space exactly when every family of sets open in (R,dR) whose union contains K has a finite subfamily whose union contains K. By [L1] the sets open in (R,dR) are exactly the open subsets of R in the sense of Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen. So the displayed condition is word for word the definition of compactness of K in [L9].

L1L8L9
2.1

Clause 1. Fix c∈A. Substituting the identities of step 1.1 into [L3], with X:=(A,dA), Y:=(R,dR) and a:=c, turns metric continuity at c into: for every real ε>0 there is a real δ>0 such that every x∈A with ∣x−c∣<δ satisfies ∣f(x)−f(c)∣<ε. That is verbatim the condition of [L5] defining continuity of f at c in the sense of Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point. The two conditions are therefore the same condition, and each holds at every point of A exactly when the other does.

step 1.1L3L5
2.2

Clause 2. The same substitution in [L4] turns metric uniform continuity into: for every real ε>0 there is a real δ>0 such that all x,x′∈A with ∣x−x′∣<δ satisfy ∣f(x)−f(x′)∣<ε, which is verbatim Uniform continuity of f:A→R: one δ serving every pair of points of A as recorded in [L5].

step 1.1L4L5
2.3

Clauses 3 and 4. The same substitution in [L6] turns the Lipschitz condition into ∣f(x)−f(x′)∣≤L ∣x−x′∣ for all x,x′∈A, and the α-Hölder condition into ∣f(x)−f(x′)∣≤C ∣x−x′∣α, the power being that of Rational powers ar of a positive base and defined at x=x′ by the convention 0α=0 recorded in [L6]. Since this library gives no other definition of the two conditions for a real function on A, the displayed inequalities are what those words mean here.

step 1.1L6
2.4

Clause 5, the sequential half: convergence first. Let (xj) be a sequence with terms in K and let p∈K. By [L10] and step 1.1, convergence of (xj) to p in (K,dK) says dK(xj,p)=∣xj−p∣→0 in R; and ∣xj−p∣→0 says that for every rational ε>0 there is J with ∣∣xj−p∣−0∣=∣xj−p∣<ε for j≥J, which is verbatim the statement xj→p of [L10]. So the two convergences are the same relation.

step 1.1L10
3.1

Clause 5, the sequential half. A sequence in (K,dK) is exactly a sequence of reals with all terms in K, and by step 2.4 a subsequence of it converges to a point of K in (K,dK) exactly when it converges to that point in R. Hence "every sequence in K has a subsequence converging in (K,dK) to a point of K" and "every sequence of reals with terms in K has a subsequence converging in R to a point of K" are the same statement, which is the assertion of [L9] and Countably compact, sequentially compact and limit point compact metric spaces.

step 2.4L9L10
3.2

Clause 6. By clauses 1 to 4, the four R-native conditions are the corresponding metric conditions for the map (A,dA)→(R,dR), so the implications of [L7] hold between them verbatim; the boundedness hypothesis in the last of them is boundedness of the metric space (A,dA), which for A⊆R is boundedness of A as a set of reals, since dA(x,x′)=∣x−x′∣.

step 2.1step 2.2step 2.3L7
3.3

Clause 7. By step 1.1 and [L11], a sequence (xk) with terms in A is Cauchy in (A,dA) exactly when for every rational ε>0 there is N with ∣xm−xn∣<ε for all m,n≥N, which is verbatim the Cauchy condition of [L10] for a sequence of reals. Combining this with clause 2 and [L12] gives that a uniformly continuous f:A→R carries Cauchy sequences of A to Cauchy sequences of reals.

step 1.1step 2.2L10L11L12
4.1

Clauses 1 to 7 are proved, each by rewriting one definition into the other along the identity dA(x,x′)=∣x−x′∣ or, for clause 5, along [L8] and the agreement of the two notions of open subset of R.

step 2.1step 2.2step 2.3step 1.2step 3.1step 3.2step 3.3∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedverified 2026-09-26 (gpt-6-sol)Open item page →

Heine-Cantor in R: a continuous real function on a compact subset of R is uniformly continuous

Statement

Let K⊆R be compact (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset) and let f:K→R be continuous on K (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point). Then f is uniformly continuous on K (Uniform continuity of f:A→R: one δ serving every pair of points of A).

This theorem is stated twice in this library, on purpose. Its metric-space twin is Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous, proved there from the cover machinery of metric spaces; the proof below uses the open-cover definition of compactness in R directly. That the two statements are the same statement in two vocabularies is Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace, clauses 1, 2 and 5, immediately above.

Choice-free proof. The argument below uses the open-cover definition of compactness directly. It considers every continuity neighbourhood at once and extracts only a finite subcover, so no countable or global choice function is selected.

Facts & Assumptions

Given: A compact set K⊆R and a continuous function f:K→R.

[L1]

Continuity at x∈K means that for every η>0 there is r>0 such that ∣f(y)−f(x)∣<η whenever y∈K and ∣y−x∣<r (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

[L3]

Uniform continuity means that for every ε>0 one δ>0 works for every pair of points of K at distance less than δ (Uniform continuity of f:A→R: one δ serving every pair of points of A).

[L4]

The real absolute value satisfies the triangle inequality (The triangle inequality, Basic properties of the absolute value).

Proof

technique · direct
1.1

If K=∅, the assertion is immediate. Otherwise fix ε>0. For each pair (x,r) with x∈K, r>0, and ∣f(y)−f(x)∣<ε/2 for every y∈K satisfying ∣y−x∣<2r, put Ux,r:=(x−r,x+r). The family of all such open intervals is an open cover of K: for each x, [L1] gives the existence of at least one admissible r, and x∈Ux,r. This defines the full family by a property, without selecting one radius for each x.

givenL1
2.1

By [L2], finitely many members Ux1,r1,…,Uxm,rm cover K. Since K is nonempty, m≥1. Set δ=min⁡1≤i≤mri>0.

step 1.1L2
3.1

Let y,z∈K with ∣y−z∣<δ, and choose one index i with y∈Uxi,ri. Then ∣y−xi∣<ri<2ri and, by [L4], ∣z−xi∣≤∣z−y∣+∣y−xi∣<δ+ri≤2ri. Admissibility of (xi,ri) gives ∣f(y)−f(xi)∣<ε/2 and ∣f(z)−f(xi)∣<ε/2. Thus ∣f(y)−f(z)∣<ε. The same δ works for every such pair, proving uniform continuity by [L3].

step 1.1step 2.1L3L4∎

Remarks

CorollaryStatement: AI-adaptedProof: AI-adaptedprecheck passverified 2026-09-09 (gpt-6-astra)Open item page →

A uniformly continuous real function on a subset D⊆R extends uniquely to a uniformly continuous function on the closure of D

Statement

Assume the Axiom of Choice (The Axiom of Choice).

Let D⊆R be nonempty and let f:D→R be uniformly continuous on D (Uniform continuity of f:A→R: one δ serving every pair of points of A). Write D‾ for the closure of D in R (Interior, closure, boundary and exterior of a subset of R). Then:

  1. there is a uniformly continuous g:D‾→R with g(x)=f(x) for every x∈D;
  2. g is the only continuous function D‾→R extending f (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point).

Uniform continuity is sufficient; continuity alone is not enough. The function x↦1/x is continuous on D=(0,1), whose closure is [0,1], and no continuous g:[0,1]→R extends it. Indeed continuity at 0 would give ∣g(x)−g(0)∣<1 for all sufficiently small positive x, whereas taking also x<1/(∣g(0)∣+2) gives 1/x>∣g(0)∣+2. By this corollary, x↦1/x is therefore not uniformly continuous on (0,1).

This is the metric extension theorem, read through the dictionary. The work is done by A uniformly continuous map from a dense subspace into a complete metric space extends uniquely to a uniformly continuous map on the whole space, applied to the metric space X:=D‾ with the subspace metric, its dense subset D, and the complete target (R,dR) (R and Rn for n≥1 with the Euclidean metric are complete, componentwise from the Cauchy criterion in R); Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace translates the hypothesis and the conclusion between the two vocabularies. The extension value is uniquely defined there. Nevertheless its proof uses countable choice, supplied here by AC, both to obtain the Cantor-intersection point and to extract an approximating sequence in the uniqueness argument.

Why later pages need exactly this. The exponential and the power functions are defined on Q first and then extended to R, and the extension step is this corollary with D the rationals of an interval; that is the use for which it is stated here rather than inside an example.

Facts & Assumptions

Given: The Axiom of Choice, a nonempty set D⊆R and a function f:D→R uniformly continuous on D; X:=D‾ with the subspace metric dX of dR(x,y)=∣x−y∣.

[L3]

Density in a metric space: A⊆X is dense in X when every point of X is adherent to A, that is when every ball of X around a point of X meets A (Interior, closure, boundary, limit point, isolated point and dense subset of a metric space).

[L5]

Extension theorem: if A is dense in a metric space X, if Y is complete and if h:A→Y is uniformly continuous, then there is a uniformly continuous g:X→Y with g∣A=h, and g is the only continuous map X→Y extending h (A uniformly continuous map from a dense subspace into a complete metric space extends uniquely to a uniformly continuous map on the whole space, Uniform continuity of a map of metric spaces: one δ serving every point, Continuity of a map between metric spaces, at a point and globally, in the ε-δ form).

Proof

technique · direct
1.1

Put X:=D‾ with the subspace metric dX, so dX(x,y)=∣x−y∣ for x,y∈X; then D⊆X, and the subspace metric that D inherits from X is again d(x,y)=∣x−y∣, the same one it inherits from R. X is nonempty, since D is and D⊆D‾.

L1L2
2.1

D is dense in the metric space X. Let x∈X and let r>0 be real. By [L2] there is t∈Nr(x)∩D, and t∈D⊆X, so t lies in the ball BX(x,r)=Nr(x)∩X of X ([L1]) and in D. Hence every ball of X around a point of X meets D, which by [L3] says D is dense in X.

step 1.1L1L2L3
2.2

Transport of the hypothesis. By [L6], applied to S:=D, the uniform continuity of f on D in the sense of Uniform continuity of f:A→R: one δ serving every pair of points of A is uniform continuity of f:(D,dD)→(R,dR) as a map of metric spaces.

step 1.1L6
3.1

By [L4] the target (R,dR) is complete, so [L5] applies with A:=D, this X, Y:=R and h:=f: there is a uniformly continuous g:X→R with g(x)=f(x) for every x∈D, and g is the only continuous map X→R extending f. The assumed AC supplies the countable choices in the supplier's Cantor-intersection construction and approximating-sequence uniqueness argument.

givenstep 2.1step 2.2L4L5
4.1

Transport of the conclusion. By [L6], applied to S:=X=D‾, uniform continuity of g as a map of metric spaces is uniform continuity of g on D‾ in the sense of Uniform continuity of f:A→R: one δ serving every pair of points of A, and continuity as a map of metric spaces is continuity on D‾ in the sense of Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point. So g is uniformly continuous on D‾, extends f, and is the unique continuous extension of f to D‾: claims 1 and 2.

step 3.1L6∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

If ∣f(x)−f(y)∣≤C∣x−y∣α on an interval for some rational α>1 then f is constant

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length), let f:I→R, let C∈R with C≥0, and let α∈Q with α>1 (Order on the rationals). Suppose

∣f(x)−f(y)∣  ≤  C ∣x−y∣αfor all x,y∈I,

the power being the rational power of a nonnegative base (Rational powers ar of a positive base, with the convention 0α=0 for α>0). Then f is constant on I: f(x)=f(y) for all x,y∈I.

The hypothesis is written out, and not expressed through Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction, because it cannot be. That definition introduces the α-Hölder condition for rational α with 0<α≤1 only, and says explicitly that no claim is made about an exponent above 1. The displayed inequality is the natural extension of the formula to α>1, and this theorem is what that extension is worth: for rational 0<α≤1 the same inequality is the α-Hölder condition of Lipschitz map, α-Hölder map for rational 0<α≤1, and contraction instantiated at I⊆R by Dictionary: for A⊆R with the metric d(x,y)=∣x−y∣, continuity and uniform continuity of f:A→R agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of R is compact in the open-cover sense of R exactly when it is a compact metric subspace, clause 4, and then it makes f uniformly continuous, hence continuous (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 f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point); above 1 it makes f constant, which is why the definition stops at 1.

Order-convexity is essential. On a domain that is not order-convex the conclusion fails: on I={0}∪{1} the function f(0)=0, f(1)=1 satisfies the inequality with C=1 and any α, and is not constant. What the proof uses is that the whole segment between two points of I lies in I, so that the distance between them can be subdivided.

Facts & Assumptions

Given: An order-convex I⊆R, a function f:I→R, a real C≥0 and a rational α>1 with ∣f(x)−f(y)∣≤C∣x−y∣α for all x,y∈I. Natural numbers are identified with their canonical images in R, as elsewhere in this library.

[L1]

Order-convexity: x,y∈I with x≤z≤y gives z∈I (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L2]

Rational powers of a positive base: ar is defined for a>0 and r∈Q, with a1=a and aq/1=aq agreeing with the integer power; and 0r=0 for rational r>0 (Rational powers ar of a positive base, Existence and uniqueness of n-th roots: a unique a1/n≥0 with (a1/n)n=a, Integer powers am).

[L3]

Laws of rational exponents for a,b>0 and r,s∈Q: ar>0; ar+s=aras; (ab)r=arbr; a−r=1/ar; (ar)s=ars (Laws of rational exponents).

[L4]

Monotonicity of rational powers: for a>1 and rationals r<s one has ar<as; and for rational r>0 and 0<a<b one has ar<br (Monotonicity of r↦ar and of a↦ar).

[L5]

Finite sums: ∑k<n(ck+1−ck)=cn−c0; ∑k<nλ=nλ; and ∣∑k<nak∣≤∑k<n∣ak∣ (Laws of finite sums and finite products, Finite sums and finite products, by recursion, Triangle inequality for finite sums).

[L6]

Archimedean property: for every real t there is a natural m≥1 with t<m; and for every real η>0 there is a natural q≥1 with 1/q<η (Every complete ordered field is Archimedean, For every ε>0 in a complete ordered field there is a natural n≥1 with 1/n<ε).

[L7]

Reciprocals: 0<s≤t implies 0<1/t≤1/s, and 0<s<t implies 1/t<1/s (Inverses of positives are positive, and reciprocation reverses order).

[L8]

Absolute value and ordered-field arithmetic: ∣u∣≥0; ∣u∣=0 exactly when u=0; ∣u∣=u for u≥0; the order is total; a real that is ≥0 and smaller than every positive real is 0 (Basic properties of the absolute value, Ordered field, Complete ordered field (least-upper-bound property)).

Proof

technique · direct
1.1

Normalisations. Since ∣x−y∣α≥0 by [L2] and [L3], the hypothesis with the constant C implies the same inequality with the constant C+1>0; so we may and do assume C>0. Also, the hypothesis and the conclusion are symmetric in x and y and are trivial when x=y, so it suffices to prove f(x)=f(y) for x,y∈I with x<y; fix such a pair and put A:=C (y−x)α, a real with A>0 by [L3].

L2L3L8suffices: prove it for C positive and x strictly less than y
1.2

The exponent gap. Put β:=α−1, a rational with β>0. By [L6] fix a natural q≥1 with 1/q<β.

L6choose
1.3

Subdividing. Let n∈N with n≥1 and put h:=(y−x)/n>0 and tk:=x+kh for k∈N. For k≤n one has x≤tk≤y, so tk∈I by [L1]; and ∣tk+1−tk∣=h for k<n. Define the sequence c:N→R by ck:=f(tmin⁡{k,n}), so that c0=f(x), cn=f(y), and ck+1−ck=f(tk+1)−f(tk) for every k<n.

L1L8
2.1

The telescoped estimate. By [L5], f(y)−f(x)=cn−c0=∑k<n(ck+1−ck), hence ∣f(y)−f(x)∣≤∑k<n∣ck+1−ck∣=∑k<n∣f(tk+1)−f(tk)∣≤∑k<nChα=n C hα, the middle inequality being the hypothesis applied to the pair tk,tk+1 of points of I and the last equality being the constant-sum rule of [L5].

step 1.3L5
2.2

The bound can be made arbitrarily small. Let a real η>0 be given and put R:=A/η>0. By [L6] fix a natural N with Rq<N; then N≥1, since Rq>0 by [L3] and [L2]. By [L4] applied with the rational exponent 1/q>0 to the bases Rq<N, and by [L2] and [L3] which give (Rq)1/q=Rq⋅(1/q)=R1=R, we get N1/q>R.

step 1.1step 1.2L2L3L4L6choose
3.1

Rewriting the bound. By [L3], hα=((y−x)⋅n−1)α=(y−x)α (n−1)α=(y−x)α n−α, and n n−α=n1n−α=n1−α=n−β=1/nβ. Hence n C hα=A/nβ, and step 2.1 gives ∣f(y)−f(x)∣≤A/nβ for every natural n≥1.

step 1.1step 1.2step 2.1L2L3
3.2

By [L4], N1/q≤Nβ: this is an equality if N=1, since then both sides are 1 by [L3], and it is the strict inequality of [L4] for the base N>1 and the exponents 1/q<β. Hence Nβ≥N1/q>R>0, so 1/Nβ<1/R by [L7] and therefore A/Nβ<A/R=η.

step 1.2step 2.2L3L4L7
4.1

Combining steps 3.1 and 3.2, ∣f(y)−f(x)∣≤A/Nβ<η. The real η>0 was arbitrary and ∣f(y)−f(x)∣≥0, so ∣f(y)−f(x)∣=0 by [L8], that is f(y)=f(x). Since x<y in I were arbitrary, and by the reduction of step 1.1, f is constant on I.

step 1.1step 3.1step 3.2L8∎

Remarks

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passverified 2026-09-09 (gpt-6-astra)Open item page →

Rudin 4.20, the sharp converse: on a noncompact E⊆R there is an unbounded continuous function and a bounded continuous function with no greatest value, and if E is bounded there is a continuous function on E that is not uniformly continuous

Statement

Let E⊆R be nonempty and not compact (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset). Then:

  1. there is a function f:E→R, continuous on E (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point), that is unbounded on E;
  2. there is a function g:E→R, continuous and bounded on E, such that sup⁡g[E] exists and is not attained; in particular g has no greatest value on E (Maximum and minimum of a set);
  3. if in addition E is bounded (Lower bound, bounded below, bounded set), there is a function h:E→R, continuous on E, that is not uniformly continuous on E (Uniform continuity of f:A→R: one δ serving every pair of points of A).

Together with A continuous real function on a compact subset of R is bounded, Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value and Heine-Cantor in R: a continuous real function on a compact subset of R is uniformly continuous this says that compactness is exactly the hypothesis needed for universal boundedness and attainment of extrema. On a compact set every continuous function is also uniformly continuous. The converse for uniform continuity asserted here applies to bounded sets.

Claim 3 carries the boundedness hypothesis because it must. On an unbounded closed uniformly discrete set, every function is uniformly continuous: if distinct points are separated by a fixed positive distance c, take δ=c for every ε>0, so ∣x−y∣<δ forces x=y. Thus claim 3 cannot be asserted for all unbounded sets. Claims 1 and 2 still hold without the boundedness hypothesis.

Every witness is exhibited, not merely asserted to exist. Four functions do the work: x and −1/(1+x2) when E is unbounded, and 1/(x−x0) and −∣x−x0∣ when E is bounded, where x0 is then a point of E‾∖E.

Facts & Assumptions

Given: A nonempty set E⊆R that is not compact.

[L2]

Boundedness: S is bounded when there are reals ℓ,u with ℓ≤s≤u for every s∈S; equivalently when there is a real M≥0 with ∣s∣≤M for every s∈S. So if S is unbounded then for every real M>0 some s∈S has ∣s∣>M (Lower bound, bounded below, bounded set, Basic properties of the absolute value, Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set).

[L4]

Algebra of continuous functions: constants, the identity and polynomial functions are continuous on any subset of R; sums, scalar multiples, products and absolute values of continuous functions are continuous; and if q is continuous on S and q(x)≠0 for every x∈S, then p/q is continuous on S (Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function, Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point, Integer powers am).

[L5]

Suprema: a nonempty subset of R bounded above has a least upper bound (Complete ordered field (least-upper-bound property)), and for u=sup⁡S every real ε>0 admits s∈S with u−ε<s (Epsilon characterisation of the supremum).

[L6]

Archimedean property in reciprocal form, reciprocals, and squares: for every real η>0 there is a natural n≥1 with 1/n<η; 0<s<t implies 0<1/t<1/s; 0≤a<b implies a2<b2; and t≥1 implies t2≥t (For every ε>0 in a complete ordered field there is a natural n≥1 with 1/n<ε, Every complete ordered field is Archimedean, Inverses of positives are positive, and reciprocation reverses order, Monotonicity of x↦xn and of n↦an, Integer powers am).

[L7]

Uniform continuity requires one positive δ for all pairs at each positive ε (Uniform continuity of f:A→R: one δ serving every pair of points of A). The triangle inequality gives ∣u−v∣≥∣u∣−∣v∣ by applying it to u=(u−v)+v (The triangle inequality).

[L8]

Ordered-field arithmetic in R: totality and trichotomy; ∣u∣>0 exactly when u≠0; 1+t2≥1>0 for every real t; and the minimum of a two-element set of reals (Ordered field, Basic properties of the absolute value, Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set, Intervals of R: the nine order-convex forms, nondegeneracy, and length).

Proof

technique · constructive
1.1

By [L1] the set E is not closed or not bounded, and these two possibilities are exhaustive: if E is bounded then it is not closed. The two cases below are treated separately, and claim 3 arises only in the second.

L1
1.2

First case: E is unbounded. Claim 1. Put f(x):=x, continuous on E by [L4]. Given a real M>0, [L2] supplies x∈E with ∣x∣>M, that is ∣f(x)∣>M; so f is unbounded on E.

L2L4construct
1.3

First case, claim 2. Put g(x):=−1/(1+x2). The denominator is a polynomial function, continuous by [L4], and satisfies 1+x2≥1>0 by [L8], so g is continuous on E by [L4]; moreover 0<1/(1+x2)≤1, so −1≤g(x)<0 for every x∈E and g is bounded. Hence g[E] is nonempty and bounded above by 0, so u:=sup⁡g[E] exists by [L5] and u≤0.

L4L5L8construct
2.1

First case: the supremum is 0 and is not attained. Let a real ε>0 be given and put M:=max⁡{1,1/ε}≥1. By [L2] there is x∈E with ∣x∣>M, so x2>M2≥M≥1/ε by [L6] and [L8], hence 1+x2>1/ε>0 and 1/(1+x2)<ε by [L6], that is g(x)>−ε. So no real below 0 is an upper bound of g[E], and 0 is one; therefore u=0. Since g(x)<0 for every x∈E by step 1.3, the value 0 is not attained, and for each x∈E the number ε:=−g(x)>0 produces by [L5] some x′∈E with g(x′)>−ε=g(x), so g has no greatest value.

step 1.3L2L5L6L8
2.2

Second case: E is bounded, hence not closed. By [L3] we have E⊆E‾ and E≠E‾, so there is x0∈E‾∖E. Every neighbourhood of x0 meets E by [L3]; and x−x0≠0 for every x∈E, since x0∉E, so ∣x−x0∣>0 there by [L8].

step 1.1L3L8choose
3.1

Second case, claim 1. Put f(x):=1/(x−x0) for x∈E. The denominator is a polynomial function, continuous by [L4], and does not vanish on E by step 2.2, so f is continuous on E by [L4]. Given a real M>0, step 2.2 supplies x∈E with ∣x−x0∣<1/M, and ∣x−x0∣>0, so ∣f(x)∣=1/∣x−x0∣>M by [L6]. Hence f is unbounded on E.

step 2.2L4L6construct
3.2

Second case, claim 2. Put g(x):=−∣x−x0∣ for x∈E, continuous on E by [L4]. Since E is bounded, [L2] gives a real M≥0 with ∣x∣≤M on E, so ∣x−x0∣≤M+∣x0∣ and −(M+∣x0∣)≤g(x)<0 for every x∈E: g is bounded, and g[E] is nonempty and bounded above by 0. For a real ε>0, step 2.2 supplies x∈E with ∣x−x0∣<ε, that is g(x)>−ε; so sup⁡g[E]=0 by [L5], and it is not attained because g(x)<0 everywhere on E. As in step 2.1, g therefore has no greatest value on E.

step 2.1step 2.2L2L4L5L8construct
4.1

Second case, claim 3. Put h:=f of step 3.1, continuous on E. Fix any δ>0. By step 2.2 choose y∈E with ∣y−x0∣<δ/2, and then choose x∈E with ∣x−x0∣<min⁡{δ/2,1/(∣h(y)∣+2)}. These are two finite selections. The triangle inequality gives ∣x−y∣<δ, while ∣h(x)∣=1/∣x−x0∣>∣h(y)∣+2. Hence ∣h(x)−h(y)∣≥∣h(x)∣−∣h(y)∣>2. Thus every positive δ fails the uniform-continuity condition for ε=1, proving claim 3.

step 2.2step 3.1L6L7L8
5.1

The two cases of step 1.1 are exhaustive, and in each of them claims 1 and 2 have been established by exhibiting the functions named, while claim 3, whose hypothesis places E in the second case, is step 4.1.

step 1.2step 1.3step 2.1step 3.1step 3.2step 4.1discharge-construct: the four witnesses x and -1/(1+x^2) and 1/(x-x_0) and -|x-x_0|∎

Remarks

  • The bounded non-closed case is where all three failures happen at once. There x0∈E‾∖E is a hole in the domain, and 1/(x−x0) blows up at it: it is unbounded, it is not uniformly continuous, and −∣x−x0∣ approaches its supremum 0 without reaching it. The unbounded case needs a different witness for claim 2, because −∣x−x0∣ need not be bounded there, and −1/(1+x2) is the standard substitute.

  • Claim 3 uses only two nearby points for each proposed radius. Adherence supplies each point in turn, and the reciprocal estimate separates their function values. This finite selection argument requires no Axiom of Choice.

  • What "not attained" means here, precisely. The supremum of g[E] exists as a real number and equals 0, and no point of E has g-value 0. That is stronger than saying g has no maximum: it identifies the value the function fails to reach. The companion page works both witnesses out concretely in The identity on (0,1) is bounded with no greatest value, and on [0,∞) it is continuous and unbounded ↗.

5 · Examples, counterexamples and false statements

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

FALSE: every continuous real function is uniformly continuous on its domain

Statement

False claim: if A⊆R and f:A→R is continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point), then f is uniformly continuous on A (Uniform continuity of f:A→R: one δ serving every pair of points of A).

Why it is tempting. Continuity says that for every ε>0 and every point c there is a δ>0 that works at c. It is easy to read that as producing "a δ", forgetting that the δ was produced after c was fixed and may depend on it. Uniform continuity demands one δ before any point is named, and the two quantifier orders are genuinely different.

What is true. On a compact domain the implication does hold, and that is Heine-Cantor in R: a continuous real function on a compact subset of R is uniformly continuous; the metric-space form is Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous. Compactness is not a convenience there: for every noncompact bounded E⊆R there is a continuous function on E that is not uniformly continuous, which is Rudin 4.20, the sharp converse: on a noncompact E⊆R there is an unbounded continuous function and a bounded continuous function with no greatest value, and if E is bounded there is a continuous function on E that is not uniformly continuous. The witness below is the smallest familiar instance of that theorem.

Facts & Assumptions

Given: The domain A:=(0,1)={ x∈R:0<x<1 } (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and the function f:A→R, f(x):=1/x. Natural numbers are identified with their canonical images in R.

[L1]

Continuity on A and uniform continuity on A, in the forms of Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point and Uniform continuity of f:A→R: one δ serving every pair of points of A; in particular, f fails to be uniformly continuous on A as soon as some real ε0>0 admits, for every real δ>0, a pair x,x′∈A with ∣x−x′∣<δ and ∣f(x)−f(x′)∣≥ε0.

[L2]

Algebra of continuous functions: the identity is continuous on A, and if q is continuous on A and does not vanish there then 1/q is continuous on A (Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function).

[L3]

Archimedean property in reciprocal form: for every real η>0 there is a natural k≥1 with 1/k<η; and 0<s<t implies 0<1/t<1/s (For every ε>0 in a complete ordered field there is a natural n≥1 with 1/n<ε, Every complete ordered field is Archimedean, Inverses of positives are positive, and reciprocation reverses order).

[L4]

Ordered-field arithmetic in R: for a natural k, 0<1/(k+3)<1/(k+2)<1, so both lie in (0,1); the product (k+2)(k+3)≥k+2≥2; and ∣u∣≥0 with ∣u∣=u for u≥0 (Ordered field, Basic properties of the absolute value, Integer powers am).

Refutation

technique · direct
1.1

f is continuous on A. The identity is continuous on A by [L2] and does not vanish on A, since x>0 for x∈(0,1); so f(x)=1/x is continuous on A by [L2].

L2L4
1.2

For k∈N put xk:=1/(k+2) and yk:=1/(k+3). By [L4] both lie in (0,1)=A, and f(xk)=k+2, f(yk)=k+3. Note that N contains 0, so the smallest pair is x0=1/2 and y0=1/3, and no index k produces a point outside A.

L4
2.1

The gap between the arguments is ∣xk−yk∣=1/(k+2)−1/(k+3)=1/((k+2)(k+3))≤1/(k+2), using (k+2)(k+3)≥k+2>0 and [L3]. The gap between the values is ∣f(xk)−f(yk)∣=∣(k+2)−(k+3)∣=1.

step 1.2L3L4
3.1

Take ε0:=1 and let a real δ>0 be given. By [L3] there is a natural m≥1 with 1/m<δ; put k:=m, so k+2>m>0 and hence 1/(k+2)<1/m<δ by [L3]. Then ∣xk−yk∣≤1/(k+2)<δ while ∣f(xk)−f(yk)∣=1≥ε0.

step 2.1L3choose
4.1

So no δ>0 serves ε0=1: by [L1] the function f is continuous on A and not uniformly continuous on A, and the claim is false.

step 1.1step 3.1L1∎

Remarks

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-27Open item page →

FALSE: the image of a closed subset of R under a continuous real function is closed

Statement

False claim: if A⊆R, if f:A→R is continuous on A (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point) and if F⊆A is a closed subset of R (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen), then the image f[F]={ f(x):x∈F } is a closed subset of R.

Why it is tempting. Continuity is characterised by the behaviour of preimages: the preimage of every closed set is relatively closed (f:A→R is continuous on A if and only if the preimage of every open subset of R is the intersection with A of an open subset of R, and dually for closed sets). It is easy to transpose that to images, and images are exactly where the characterisation says nothing.

What is true. Compactness, not closedness, is preserved: the image of a compact set under a continuous function is compact (The image of a compact subset of R under a continuous real function is compact), hence closed and bounded (A subset of R is compact if and only if it is closed and bounded). Closedness by itself is preserved by neither images nor unions of infinitely many closed sets, and boundedness by itself is not preserved either, since x↦1/x carries the bounded set (0,1) onto the unbounded set (1,∞).

Facts & Assumptions

Given: The domain A:=R, the closed set F:=R, and the function f:R→R, f(x):=1/(1+x2) (Integer powers am).

[L1]
[L3]

Squares and order: x2≥0 for every real x, so 1+x2≥1>0; and 0<s≤t implies 0<1/t≤1/s (Monotonicity of x↦xn and of n↦an, Inverses of positives are positive, and reciprocation reverses order, Ordered field, Integer powers am).

[L4]

Square roots: every real t≥0 has a unique s≥0 with s2=t (Existence and uniqueness of n-th roots: a unique a1/n≥0 with (a1/n)n=a).

[L6]

Intervals and minima: (0,1]={ y:0<y≤1 } (Intervals of R: the nine order-convex forms, nondegeneracy, and length); the minimum of a two-element set of reals exists and is one of them (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set); and ∣u∣≥0 with ∣u∣=u for u≥0 (Basic properties of the absolute value).

Refutation

technique · direct
1.1

F=R is a closed subset of R and is contained in A=R.

L1
1.2

f is continuous on R: the denominator x↦1+x2 is a polynomial function, hence continuous by [L2], and it satisfies 1+x2≥1>0 by [L3], so it never vanishes and f=1/(1+x2) is continuous by [L2].

L2L3
1.3

(0,1]⊆f[R]. Let y satisfy 0<y≤1 and put t:=1/y−1. By [L3] we have 1/y≥1, so t≥0, and [L4] supplies a real s≥0 with s2=t. Then 1+s2=1/y and hence f(s)=1/(1+s2)=y.

L3L4L6
1.4

(0,1] is not closed. Let a real ε>0 be given and put y:=min⁡{ε/2, 1}, a real with 0<y≤1 by [L6], so y∈(0,1]; and ∣y−0∣=y≤ε/2<ε, so y∈Nε(0)∩(0,1]. Hence 0∈(0,1]‾ by [L5], while 0∉(0,1] because 0<0 is false. So (0,1]≠(0,1]‾ and (0,1] is not closed by [L5].

L5L6
2.1

f[R]⊆(0,1]. For every real x, [L3] gives 1+x2≥1>0 and hence 0<1/(1+x2)≤1, that is f(x)∈(0,1].

step 1.2L3L6
3.1

So f[F]=f[R]=(0,1].

step 2.1step 1.3
4.1

The set F=R is closed, f is continuous on R, and f[F]=(0,1] is not closed: the claim is false.

step 1.1step 1.2step 3.1step 1.4∎

Remarks

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passverified 2026-08-09 (gpt-5.6-terra-codex-subscription)Open item page →

FALSE: a continuous real function on a bounded domain attains a greatest value

Statement

False claim: if E⊆R is nonempty and bounded (Lower bound, bounded below, bounded set) and f:E→R is continuous on E (Continuity of f:A→R at a point of A and on A: the ε-δ condition, its agreement with lim⁡x→cf(x)=f(c) at a limit point, and continuity at an isolated point), then f attains a greatest value on E: there is p∈E with f(x)≤f(p) for every x∈E (Maximum and minimum of a set).

Why it is tempting. The extreme value theorem is often remembered as "a continuous function on a bounded interval attains its bounds", and on [a,b] that is true. The hypothesis that actually does the work is compactness, which for a subset of R is closed and bounded (A subset of R is compact if and only if it is closed and bounded); dropping closedness loses the theorem even though the function may stay bounded.

What is true. Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value gives the conclusion on a nonempty compact domain, and the hypothesis cannot be weakened: for every noncompact E there is a bounded continuous function on E whose supremum is not attained, which is Rudin 4.20, the sharp converse: on a noncompact E⊆R there is an unbounded continuous function and a bounded continuous function with no greatest value, and if E is bounded there is a continuous function on E that is not uniformly continuous. The witness below is that theorem's simplest instance.

Facts & Assumptions

Given: The domain E:=(0,1)={ x∈R:0<x<1 } (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and the function f:E→R, f(x):=x.

[L1]

E is nonempty and bounded: 1/2∈E, and 0≤x≤1 for every x∈E (Lower bound, bounded below, bounded set, Intervals of R: the nine order-convex forms, nondegeneracy, and length, Ordered field).

[L3]

A greatest value of f on E is a point p∈E with f(x)≤f(p) for every x∈E; equivalently a maximum of f[E] lying in f[E] (Maximum and minimum of a set).

[L4]

Ordered-field arithmetic in R: for 0<x<1 one has x<(x+1)/2<1; and 0<1 (Ordered field).

[L5]

Suprema: a nonempty set bounded above has a least upper bound, and for u=sup⁡S every real ε>0 admits s∈S with u−ε<s (Complete ordered field (least-upper-bound property), Epsilon characterisation of the supremum).

Refutation

technique · direct
1.1

E is nonempty and bounded by [L1], and f is continuous on E by [L2], so the hypotheses of the claim are satisfied.

L1L2
2.1

Let p∈E be arbitrary, so 0<p<1. Put p′:=(p+1)/2; by [L4] we have p<p′<1 and 0<p′, so p′∈E and f(p′)=p′>p=f(p). Hence no p∈E satisfies f(x)≤f(p) for every x∈E, and by [L3] the function f attains no greatest value on E.

step 1.1L3L4
3.1

The claim is therefore false. Note also what the failure is not: f[E]=E is nonempty and bounded above by 1, so sup⁡f[E] exists by [L5] and equals 1, since 1 bounds f[E] and for every real ε>0 the point x:=max⁡{1/2, 1−ε/2} lies in E with x>1−ε. What fails is only that 1∉f[E].

step 2.1L1L4L5∎

Remarks

Sources