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.

✓ 23 results · all verified · 18 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 5 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Monotone Functions, Discontinuities, and Continuity Sets

1 · Prerequisites

2 · Summary

Objective. A function of a real variable can fail to be continuous in only so many ways, and this page measures the failure. It asks three questions and answers each of them completely. Which sets are the discontinuity sets of a monotone function? Which sets are the continuity sets of an arbitrary function? And which functions satisfying Cauchy's equation f(x+y)=f(x)+f(y) are the obvious ones? The answers are: exactly the at most countable sets; exactly the Gδ sets; and exactly those with any one of six very weak regularity properties.

Monotone functions. Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences fixes the vocabulary — nondecreasing, increasing, nonincreasing, decreasing, monotone, strictly monotone — in the same convention Nondecreasing, increasing, nonincreasing, decreasing, monotone, and eventually monotone sequences uses for sequences, and records the dictionary between the two. The first theorem, One-sided limits of a monotone function always exist: for f nondecreasing on an interval I and c∈I, lim⁡x→c−f(x)=sup⁡{f(x):x∈I, x<c} whenever I has points below c, lim⁡x→c+f(x)=inf⁡{f(x):x∈I, x>c} whenever it has points above c, and these satisfy lim⁡x→c−f(x)≤f(c)≤lim⁡x→c+f(x), is the one everything else on this half of the page rests on: a monotone function on an interval has every well-posed one-sided limit. For a nondecreasing function the left limit is a supremum and the right limit an infimum; for a nonincreasing function the roles reverse. Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind then sorts discontinuities into removable, jump and essential, equivalently Rudin's first and second kind, and A monotone function on an interval has no discontinuity of the second kind: at every point both relevant one-sided limits exist, and an interior point c is a discontinuity exactly when lim⁡x→c−f(x)<lim⁡x→c+f(x) shows that a monotone function has none of the second kind: at an interior point it is discontinuous exactly when the two one-sided limits differ, and then it jumps.

Froda's theorem and its converse. Froda's theorem: the set of discontinuities of a monotone function on an interval is at most countable, the injection into N being built from one fixed enumeration of the rationals by least index, so no choice principle is used counts those jumps: the discontinuity set of a monotone function on an interval is at most countable, because the open intervals it opens between its one-sided limits are pairwise disjoint and each swallows a rational. The proof uses one fixed enumeration of Q and least indices, so it spends no choice principle. Converse to Froda: for every at most countable E⊆R there is a bounded nondecreasing f:R→R whose set of discontinuities is exactly E, every one of them a jump is the exact converse: for every at most countable E⊆R there is a bounded nondecreasing function on R discontinuous exactly on E, with every discontinuity a jump. Together the two settle the first question with no gap.

Continuous injections and inverses. A continuous injective function on an interval is strictly monotone proves that a continuous injection on an interval cannot fold: the middle of any three points carries the middle value, and strict monotonicity follows. Continuous inverse theorem: a continuous injective f on an interval I is a bijection onto the order-convex set f[I], and the inverse g:f[I]→I is continuous and strictly monotone in the same sense as f then delivers the continuous inverse theorem — the inverse of a continuous injection on an interval is continuous and monotone in the same sense — with no epsilon-delta argument, by reading it off A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous. The same lemma gives The Cantor function is continuous on [0,1], which supplies the continuity that The Cantor function is well defined, satisfies c(x)≤c(y) whenever x≤y, is surjective onto [0,1], and is constant on every interval removed from the Cantor set deliberately left unclaimed, and The Cantor function is continuous and nondecreasing, climbs from 0 to 1, and is constant on every interval removed in the construction of the Cantor set, so all of its increase happens on a set of measure zero records what that continuity sits alongside: the function climbs from 0 to 1 while being locally constant off a set of measure zero.

Oscillation, and the continuity set. The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals introduces ωf, valued in the extended reals so that no boundedness hypothesis is needed, and f:A→R is continuous at c∈A if and only if ωf(c)=0 converts continuity at a point into the vanishing of a single number there. That is what makes the continuity set accessible: For every real ε>0 the set { x∈A:ωf(x)≥ε } is the intersection with A of a closed subset of R; in particular it is closed in R when A=R shows each set {ωf≥ε} is relatively closed, and For f:A→R the set of points of A at which f is discontinuous is the intersection with A of an Fσ subset of R, and the set of points at which f is continuous is the intersection with A of a Gδ subset; for A=R the two sets are Fσ and Gδ outright assembles them, first into the pointwise exhaustion of the discontinuity set by the superlevel sets at the thresholds 1,1/2,1/3,…, and then into the statement that the discontinuity set is Fσ and the continuity set Gδ. Both halves are cited downstream, and the exhaustion is stated as a claim in its own right for that reason. Every Gδ subset of R is the set of continuity points of some f:R→R, so the Gδ sets are exactly the continuity sets proves the converse, so the continuity sets are exactly the Gδ sets, and No function R→R is continuous at every rational and discontinuous at every irrational, because Q is not Gδ spends that on the sharpest consequence: no function is continuous at every rational and discontinuous at every irrational, because Q is not Gδ (Q is Fσ, meager and not Gδ, while the irrationals are Gδ, residual and not Fσ).

Dirichlet and Thomae. The Dirichlet function 1Q, and Thomae's function t with t(x)=1/q at a rational x=p/q in lowest terms with q≥1 and t(x)=0 at every irrational x defines the indicator of the rationals and Thomae's function, the latter through the least denominator, which is a least element of a set of naturals and therefore canonical. The Dirichlet function is continuous at no point of R, and Thomae's function is continuous at every irrational and at no rational, so its set of continuity points is exactly the set of irrationals and its oscillation at c equals t(c) proves that the first is continuous nowhere, that the second is continuous exactly at the irrationals, and that its oscillation at a point equals its value there. Thomae's function is the witness that the arrangement forbidden by No function R→R is continuous at every rational and discontinuous at every irrational, because Q is not Gδ is possible the other way round. Both functions are defined here rather than on the companion page because later pages need them, and an examples page is a leaf of this library; the Dirichlet clause deliberately restates, across that boundary, what The indicator of Q is continuous at no point of R already proves.

The intermediate value property. The intermediate value property (Darboux property) of a function on an interval: the image of every subinterval is order-convex names the Darboux property and proves the equivalence of its two usual forms. Every continuous function on an interval has it; the converse is false, and FALSE: a function with the intermediate value property on an interval is continuous refutes it with a witness built by hand from the distance to the nearest integer.

Semicontinuity. Upper and lower semicontinuity of f:A→R at a point of A and on A splits continuity into its two halves, f is upper semicontinuous on A if and only if {x∈A:f(x)<α} is relatively open in A for every real α, lower semicontinuous if and only if {x∈A:f(x)>α} is, and continuous if and only if it is both identifies each half by its level sets, and Semicontinuous extreme value theorem: an upper semicontinuous function on a nonempty compact K⊆R is bounded above and attains a maximum, and a lower semicontinuous one is bounded below and attains a minimum proves the semicontinuous extreme value theorem: an upper semicontinuous function on a nonempty compact set attains a maximum. The theorem is genuinely one-sided, and the companion page says why.

Baire class one. Baire category inside a closed bounded interval: if [a,b] with a<b is covered by a sequence of closed sets, then one of them contains a nondegenerate closed subinterval of [a,b]; no choice principle is used localises Baire category in R, by nested intervals with canonically chosen rational endpoints: a countable intersection of dense open sets is dense, so R is not a countable union of nowhere dense sets to a closed bounded interval, which is the form the next theorem needs. Pointwise convergence of a sequence of real functions, and the Baire class one functions as the pointwise limits of sequences of continuous functions defines pointwise convergence and the pointwise limits of continuous functions, and Baire's theorem: a Baire class one function on a closed bounded interval [a,b] is continuous at the points of a dense subset of [a,b] that is the trace of a Gδ set, so its set of discontinuities is meager proves Baire's theorem: such a function on [a,b] has a meager discontinuity set and is continuous on a dense subset. The argument is the refinement claim — on every subinterval there is a smaller one where the oscillation is small — repeated through category.

Cauchy's functional equation. Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R states the equation, An additive f:R→R satisfies f(0)=0, f(−x)=−f(x) and f(qx)=q f(x) for every rational q and every real x; in particular f(q)=q f(1) at every rational q proves that an additive function is Q-homogeneous and hence determined on Q by its value at 1, and If an additive f:R→R is bounded above on some nondegenerate interval, then f(x)=f(1) x for every real x is the engine: one upper bound on one nondegenerate interval already forces f(x)=f(1)x everywhere. Six regularity conditions each force an additive f:R→R to be x↦f(1)x: continuity at a single point, monotonicity on a nondegenerate interval, boundedness above on one, boundedness below on one, constancy of sign on one, and a graph that is not dense in R2 collects six conditions that each imply linearity — continuity at a single point, monotonicity on an interval, boundedness above or below on one, constancy of sign on one, and a graph that is not dense in R2 — five of them by reduction to that lemma. Two further classical clauses, boundedness on a set of positive measure and Lebesgue measurability, are absent: both need a measure, which is not available at this point in the reading order, and each is an independent sufficient condition, so nothing else changes when they are restored.

And what happens without any of them. Assuming the Axiom of Choice, R has a Hamel basis over Q: there is B⊆R such that every real is a finite Q-linear combination of elements of B in exactly one way, and each basis vector carries a well-defined Q-linear coefficient map produces, from the Axiom of Choice through Every vector space has a basis and Zorn's lemma, a basis of R over Q together with the coefficient map of a single basis vector; that map is additive and takes only rational values, which refutes FALSE: every additive f:R→R is of the form x↦cx for a single real c outright. The hypothesis of choice is carried explicitly in the statement of every item that uses it. The lemma is stated here rather than quoted from R as a vector space over Q has a basis, and every such basis is infinite; the existence proof exhibits none because that item lives on an examples page, which is a leaf; the two statements are not the same, and the lemma says exactly how they differ.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences

Definition

Throughout, R is the complete ordered field (Complete ordered field (least-upper-bound property), Ordered field) with its order (Order on the reals). Let A⊆R and let f:A→R. Then f is:

  • nondecreasing when f(x)≤f(y) for all x,y∈A with x≤y;
  • increasing, or strictly increasing, when f(x)<f(y) for all x,y∈A with x<y;
  • nonincreasing when f(x)≥f(y) for all x,y∈A with x≤y;
  • decreasing, or strictly decreasing, when f(x)>f(y) for all x,y∈A with x<y;
  • monotone when it is nondecreasing or nonincreasing;
  • strictly monotone when it is increasing or decreasing.

The naming follows the convention of Nondecreasing, increasing, nonincreasing, decreasing, monotone, and eventually monotone sequences, which is the convention of this library throughout: increasing is the strict notion and nondecreasing the weak one.

An increasing function is nondecreasing, and a decreasing function is nonincreasing. For x≤y either x<y, and then f(x)<f(y), hence f(x)≤f(y); or x=y, and then f(x)=f(y). The same argument with the inequalities reversed gives the second claim. So strictly monotone implies monotone.

A strictly monotone function is injective (Injection, surjection, bijection). Let f be increasing and let x,y∈A with x≠y. By trichotomy either x<y, and then f(x)<f(y), or y<x, and then f(y)<f(x); in both cases f(x)≠f(y). The decreasing case is the same argument. The converse fails, and the failure is not exotic: a continuous injection on an interval is strictly monotone (A continuous injective function on an interval is strictly monotone), but on a domain that is not an interval it need not be.

Negation exchanges the two directions. For g:=−f, that is g(x):=−f(x), the four conditions above are exchanged in pairs: f is nondecreasing exactly when g is nonincreasing, and f is increasing exactly when g is decreasing, because u≤v holds exactly when −v≤−u (Ordered field). Several proofs below use this to reduce a nonincreasing case to a nondecreasing one.

Monotone on a set, not at a point. All six conditions are conditions on the whole of A; unlike continuity (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) there is no pointwise version, and none is used in this library. The domain A is an arbitrary subset of R; where a result needs A to be an interval (Intervals of R: the nine order-convex forms, nondegeneracy, and length) it says so, and the hypothesis is never decoration.

The dictionary to monotone sequences

A sequence of reals is a function x:N→R (Sequences of reals: bounded, eventually, frequently, tails, subsequences), and Nondecreasing, increasing, nonincreasing, decreasing, monotone, and eventually monotone sequences calls it nondecreasing when xj≤xk for all j≤k, increasing when xj<xk for all j<k, and so on. Those are the same four conditions as above, read with the ordered set N in place of the ordered subset A⊆R and with the comparison of indices in place of the comparison of arguments. So nothing new is introduced here for sequences, and the two vocabularies may be used interchangeably: the words nondecreasing, increasing, nonincreasing, decreasing, monotone and strictly monotone mean the corresponding condition on the domain at hand.

One consequence is used repeatedly, and it has to be stated carefully because composition does not simply preserve the four words. Let (xk) be a nondecreasing sequence with xk∈A for every k, so that j≤k gives xj≤xk. Then:

  • if f is nondecreasing, (f(xk)) is nondecreasing, since f(xj)≤f(xk);
  • if f is nonincreasing, (f(xk)) is nonincreasing, since f(xj)≥f(xk).

So along a nondecreasing sequence the composite inherits the direction of f; and with (xk) increasing and f increasing, (f(xk)) is increasing, while with (xk) increasing and f decreasing, (f(xk)) is decreasing.

Along a nonincreasing sequence the direction is reversed, not inherited. If (xk) is nonincreasing and f is nonincreasing, then j≤k gives xj≥xk and hence f(xj)≤f(xk): the composite is nondecreasing. The witness is f(x)=−x on A=R with xk=−k, where both f and (xk) are decreasing and f(xk)=k is increasing. Two order-reversing maps compose to an order-preserving one, exactly as for the four words applied to functions.

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

One-sided limits of a monotone function always exist: for f nondecreasing on an interval I and c∈I, lim⁡x→c−f(x)=sup⁡{f(x):x∈I, x<c} whenever I has points below c, lim⁡x→c+f(x)=inf⁡{f(x):x∈I, x>c} whenever it has points above c, and these satisfy lim⁡x→c−f(x)≤f(c)≤lim⁡x→c+f(x)

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length), let f:I→R be nondecreasing (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences) and let c∈I. Write

I−:=I∩(−∞,c),I+:=I∩(c,∞)

(The left and right limits of f at c, as limits of the restrictions of f to A∩(−∞,c) and A∩(c,∞)).

  1. Left. If I−≠∅ then c is a limit point of I− (Limit point, isolated point, adherent point, derived set, and dense subset of R), the set { f(x):x∈I− } is nonempty and bounded above by f(c), and lim⁡x→c−f(x)  =  sup⁡{ f(x):x∈I, x<c }  ≤  f(c).
  2. Right. If I+≠∅ then c is a limit point of I+, the set { f(x):x∈I+ } is nonempty and bounded below by f(c), and lim⁡x→c+f(x)  =  inf⁡{ f(x):x∈I, x>c }  ≥  f(c).
  3. Together. If both I− and I+ are nonempty then lim⁡x→c−f(x)  ≤  f(c)  ≤  lim⁡x→c+f(x).

In particular a nondecreasing function on an interval has, at every point of that interval, every one-sided limit that is well posed at all: no hypothesis of continuity, of boundedness, or of any other kind is needed.

The nonincreasing case is not a separate theorem. If g:I→R is nonincreasing then −g is nondecreasing (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences), and a real L is the left limit of −g at c exactly when −L is the left limit of g at c, since ∣(−g)(x)−L∣=∣g(x)−(−L)∣; so claims 1 to 3 hold for g with the suprema and infima exchanged and the inequalities reversed.

Order-convexity of I is what makes the limits well posed. Without it the symbol lim⁡x→c−f(x) need not be defined even though I− is nonempty: for I={0}∪[1,2] and c=1 the set I−={0} is nonempty but 1 is not a limit point of it, and The left and right limits of f at c, as limits of the restrictions of f to A∩(−∞,c) and A∩(c,∞) leaves the symbol undefined there for exactly that reason.

Facts & Assumptions

Given: An order-convex I⊆R, a nondecreasing f:I→R, and c∈I.

[A2]

I is order-convex: x,y∈I and x≤z≤y imply z∈I (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L1]

Every nonempty subset of R that is bounded above has a least upper bound, and every nonempty subset bounded below has a greatest lower bound (Complete ordered field (least-upper-bound property), Lower bound, bounded below, bounded set, Greatest lower bound (infimum), Every nonempty set bounded below has an infimum).

[L2]

For S nonempty and bounded above with upper bound u: u=sup⁡S if and only if for every real ε>0 there is s∈S with u−ε<s (Epsilon characterisation of the supremum). Dually, for S nonempty and bounded below with lower bound ℓ: ℓ=inf⁡S if and only if for every real ε>0 there is s∈S with s<ℓ+ε (Epsilon characterisation of the infimum).

[L3]

lim⁡x→c−f(x)=L means: c is a limit point of I−, and for every real ε>0 there is a real δ>0 with ∣f(x)−L∣<ε for every x∈I with c−δ<x<c; dually on the right (The left and right limits of f at c, as limits of the restrictions of f to A∩(−∞,c) and A∩(c,∞), The ε-δ limit lim⁡x→cf(x)=L of f:A→R at a limit point c of A, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L4]

x is a limit point of a set S when every punctured neighbourhood of x meets S (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); a one-sided limit, being the limit of a restriction, is unique when it exists (At a limit point of the domain a function has at most one limit).

Proof

technique · direct
1.1

Suppose I−≠∅ and fix a∈I with a<c; then [a,c]⊆I, since any z with a≤z≤c lies in I.

A2
1.2

Claim 2 is the same argument on the other side, and is written out here rather than deduced. Suppose I+≠∅ and fix b∈I with c<b; then [c,b]⊆I, and for real δ>0 the point min⁡{b,c+δ/2} lies in I+ within δ of c, so c is a limit point of I+.

A2L4
2.1

Every real δ>0 gives a point of I− within δ of c and different from c: put z:=max⁡{a,c−δ/2}, so that a≤z<c and c−z≤δ/2<δ, and z∈I by step 1.1. Hence c is a limit point of I− and the symbol on the left of claim 1 is well posed.

step 1.1L4
2.2

The set S−:={ f(x):x∈I, x<c } is nonempty, since f(a)∈S−, and f(c) is an upper bound of it, since x<c gives f(x)≤f(c). So L:=sup⁡S− exists and L≤f(c), the latter because f(c) is an upper bound and L is the least one.

step 1.1A1L1
2.3

The set S+:={ f(x):x∈I, x>c } is nonempty and bounded below by f(c), so M:=inf⁡S+ exists and M≥f(c).

step 1.2A1L1
3.1

Let ε>0 be real. By the epsilon characterisation of the supremum there is x0∈I with x0<c and L−ε<f(x0).

step 2.2L2
3.2

Given real ε>0, the epsilon characterisation of the infimum gives x1∈I with x1>c and f(x1)<M+ε; put δ:=x1−c>0. For x∈I with c<x<c+δ we have c<x<x1, so M≤f(x)≤f(x1)<M+ε and hence ∣f(x)−M∣<ε.

step 2.3A1L2
4.1

Put δ:=c−x0>0 and let x∈I satisfy c−δ<x<c. Then x0<x<c, so f(x0)≤f(x) by monotonicity and f(x)≤L because f(x)∈S− and L is an upper bound of S−; hence L−ε<f(x0)≤f(x)≤L and therefore ∣f(x)−L∣<ε.

step 2.2step 3.1A1
4.2

Claim 2 is proved: lim⁡x→c+f(x)=M=inf⁡S+≥f(c).

step 1.2step 2.3step 3.2L3L4
5.1

Claim 1 is proved: ε>0 was arbitrary in step 3.1, so lim⁡x→c−f(x)=L=sup⁡S−≤f(c), and this value is the only one the symbol can denote.

step 2.1step 2.2step 4.1L3L4
6.1

Claim 3 follows by combining the two inequalities of claims 1 and 2, both of which are then available.

step 5.1step 4.2∎

Remarks

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind

Definition

Let A⊆R, let f:A→R and let c∈A. Then f is discontinuous at c, and c is a discontinuity of f, when f is not 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). As in The left and right limits of f at c, as limits of the restrictions of f to A∩(−∞,c) and A∩(c,∞) write

A−:=A∩(−∞,c),A+:=A∩(c,∞)

(Intervals of R: the nine order-convex forms, nondegeneracy, and length), and recall that lim⁡x→c−f(x) is defined only when c is a limit point of A−, and lim⁡x→c+f(x) only when c is a limit point of A+ (Limit point, isolated point, adherent point, derived set, and dense subset of R).

At an isolated point there is nothing to classify. If c is an isolated point of A (Limit point, isolated point, adherent point, derived set, and dense subset of R), so that A∩Nρ(c)={c} for some real ρ>0, then f is continuous at c: the ε-δ condition 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 is satisfied by δ:=ρ, since the only x∈A with ∣x−c∣<ρ is c itself and ∣f(c)−f(c)∣=0. So every discontinuity is a limit point of A, and the classification below covers every case that occurs.

Two-sided points

Suppose c is a limit point of both A− and A+, so that both one-sided limits are well posed. Say that c is a discontinuity

  • of the first kind when both one-sided limits exist;
  • of the second kind, also called essential, when at least one of the two one-sided limits fails to exist.

A discontinuity of the first kind is further

The three cases removable, jump, essential are mutually exclusive and exhaust the two-sided discontinuities of f: either both one-sided limits exist, and then they are equal or not, or one of them does not exist.

Removable is a name for what can be repaired. If c is a removable discontinuity with common one-sided value L, then the function agreeing with f off c and taking the value L at c is continuous at c, again by If c is a limit point of the domain from both sides, the limit exists iff both one-sided limits exist and agree and 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: changing the single value f(c) removes the discontinuity. No such repair is available at a jump or at an essential discontinuity, since there the two-sided limit does not exist at all and no choice of value at c can create it.

One-sided points

If c is a limit point of exactly one of A− and A+, only that side is defined and only that side is used: c is a discontinuity of the first kind when the one-sided limit on the side in question exists, and of the second kind otherwise. When it exists it is different from f(c), since on such a point the one-sided condition and the continuity condition are the same condition; and there is no jump case, there being nothing to compare the value with. The endpoints of an interval are the typical instance.

On the two vocabularies. First kind and second kind are Rudin's terms and are recorded because the literature uses them; removable, jump and essential are the names used in the rest of this library. They name the same three cases and no third classification is introduced.

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

A monotone function on an interval has no discontinuity of the second kind: at every point both relevant one-sided limits exist, and an interior point c is a discontinuity exactly when lim⁡x→c−f(x)<lim⁡x→c+f(x)

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and let f:I→R be nondecreasing (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences). Write I−=I∩(−∞,c) and I+=I∩(c,∞) for c∈I.

  1. At every c∈I, each of the two one-sided limits that is well posed exists (The left and right limits of f at c, as limits of the restrictions of f to A∩(−∞,c) and A∩(c,∞)). Consequently f has no discontinuity of the second kind (Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind): every discontinuity of f is of the first kind.
  2. Call c∈I an interior point of I when both I− and I+ are nonempty. At such a point lim⁡x→c−f(x)  ≤  f(c)  ≤  lim⁡x→c+f(x), and 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) if and only if lim⁡x→c−f(x)=lim⁡x→c+f(x).
  3. Hence an interior point c is a discontinuity of f exactly when lim⁡x→c−f(x)  <  lim⁡x→c+f(x), and every such discontinuity is a jump, of jump lim⁡x→c+f(x)−lim⁡x→c−f(x)>0.

The same three claims hold for a nonincreasing f, with the two one-sided limits exchanged and all inequalities reversed, by applying the above to −f, which is nondecreasing (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences) and has exactly the same points of continuity, since ∣(−f)(x)−(−f)(c)∣=∣f(x)−f(c)∣.

A point of I that is not interior is an endpoint, and there are at most two. I−=∅ says that c is a least element of I and I+=∅ that it is a greatest one, and a set has at most one of each. Those two points are excluded from claims 2 and 3 only because a comparison of two one-sided limits is not available there; claim 1 covers them.

Facts & Assumptions

Given: An order-convex I⊆R, a nondecreasing f:I→R, and c∈I.

[L1]

If I−≠∅ then c is a limit point of I− and lim⁡x→c−f(x)=sup⁡{f(x):x∈I,x<c}≤f(c); if I+≠∅ then c is a limit point of I+ and lim⁡x→c+f(x)=inf⁡{f(x):x∈I,x>c}≥f(c) (One-sided limits of a monotone function always exist: for f nondecreasing on an interval I and c∈I, lim⁡x→c−f(x)=sup⁡{f(x):x∈I, x<c} whenever I has points below c, lim⁡x→c+f(x)=inf⁡{f(x):x∈I, x>c} whenever it has points above c, and these satisfy lim⁡x→c−f(x)≤f(c)≤lim⁡x→c+f(x)).

[L2]

If c is a limit point of both I− and I+, then lim⁡x→cf(x)=L holds if and only if both one-sided limits at c exist and equal L; in particular the two-sided limit exists exactly when the two one-sided limits exist and agree (If c is a limit point of the domain from both sides, the limit exists iff both one-sided limits exist and agree).

[L4]

A discontinuity at a two-sided point is of the second kind when at least one one-sided limit fails to exist, of the first kind otherwise, and is a jump when the two one-sided limits exist and differ; at a one-sided point it is of the first kind when the one available one-sided limit exists (Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind).

Proof

technique · direct
1.1

Let c∈I. If I−≠∅ then lim⁡x→c−f(x) exists, and if I+≠∅ then lim⁡x→c+f(x) exists; if one of the two sets is empty the corresponding symbol is not defined and there is nothing to prove for it.

L1
2.1

Claim 1 follows: at every point of I every well-posed one-sided limit of f exists, so no discontinuity of f can be of the second kind, and every discontinuity is therefore of the first kind.

step 1.1L4
2.2

Now let c be an interior point of I, and write L−:=lim⁡x→c−f(x) and L+:=lim⁡x→c+f(x), both of which exist by step 1.1. Then L−≤f(c)≤L+, which is the displayed inequality of claim 2.

step 1.1L1
3.1

Suppose L−=L+. Then L−≤f(c)≤L+=L− forces L−=f(c)=L+, so both one-sided limits equal f(c); hence lim⁡x→cf(x) exists and equals f(c), and f is continuous at c.

step 2.2L2L3
3.2

Suppose conversely that f is continuous at c. Since c is a limit point of I− and hence of I, continuity gives lim⁡x→cf(x)=f(c), and then both one-sided limits exist and equal f(c); in particular L−=L+.

step 2.2L1L2L3
4.1

Claim 2 is proved by steps 3.1 and 3.2 together with step 2.2.

step 2.2step 3.1step 3.2
5.1

Claim 3: at an interior point c, f is discontinuous exactly when L−≠L+, and since L−≤f(c)≤L+ the only way for them to differ is L−<L+. Both one-sided limits exist and differ, so the discontinuity is a jump, of jump L+−L−>0.

step 2.2step 4.1L4∎

Remarks

  • Nothing here counts the discontinuities. Claim 3 says only what a discontinuity of a monotone function looks like at an interior point. That the set of them is at most countable is a further theorem, Froda's theorem: the set of discontinuities of a monotone function on an interval is at most countable, the injection into N being built from one fixed enumeration of the rationals by least index, so no choice principle is used, and its proof is exactly the observation that the open intervals (lim⁡x→c−f(x),lim⁡x→c+f(x)) attached to distinct discontinuities are disjoint.

  • Why no interior discontinuity of a monotone function is removable. Claim 2 rules them out at interior points: there L−=L+ already forces continuity, because the inequality L−≤f(c)≤L+ pins f(c) between the two one-sided values. That inequality is special to monotone functions, and it is what makes jump the only kind of interior discontinuity available. At a point of I that is not interior the inequality is one-sided too and the argument does not apply, so a monotone function may fail to be continuous at an endpoint of I while having its one one-sided limit; that failure is a discontinuity of the first kind and it is not a jump, there being only one side to compare.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Froda's theorem: the set of discontinuities of a monotone function on an interval is at most countable, the injection into N being built from one fixed enumeration of the rationals by least index, so no choice principle is used

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and let f:I→R be monotone (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences). Then the set

D  :=  { c∈I:f is discontinuous at c }

(Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind) is at most countable (Finite, countably infinite, countable, uncountable).

More precisely, the proof exhibits an injection J:D→N (Injection, surjection, bijection) built from one fixed enumeration of the rationals: at a discontinuity c interior to I the value J(c) is read off the least index of a rational lying in the gap (lim⁡x→c−f(x), lim⁡x→c+f(x)), which is a nonempty open interval by A monotone function on an interval has no discontinuity of the second kind: at every point both relevant one-sided limits exist, and an interior point c is a discontinuity exactly when lim⁡x→c−f(x)<lim⁡x→c+f(x). The map J is therefore determined by f and by the fixed enumeration, and no choice principle is used: least indices are canonical by The well-ordering principle, and nothing anywhere in the proof is selected without being determined.

Facts & Assumptions

Given: An order-convex I⊆R and a monotone f:I→R; and Q denotes the canonical copy of the rationals inside R.

[A1]

I is order-convex: x,y∈I and x≤z≤y imply z∈I (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L1]

A nondecreasing f on an order-convex I has, at every c∈I, each well-posed one-sided limit; and if both I−=I∩(−∞,c) and I+=I∩(c,∞) are nonempty then lim⁡x→c−f(x)=sup⁡{f(x):x∈I,x<c} and lim⁡x→c+f(x)=inf⁡{f(x):x∈I,x>c} (One-sided limits of a monotone function always exist: for f nondecreasing on an interval I and c∈I, lim⁡x→c−f(x)=sup⁡{f(x):x∈I, x<c} whenever I has points below c, lim⁡x→c+f(x)=inf⁡{f(x):x∈I, x>c} whenever it has points above c, and these satisfy lim⁡x→c−f(x)≤f(c)≤lim⁡x→c+f(x)).

[L2]

For a nondecreasing f on an order-convex I and a point c with both I− and I+ nonempty, f is discontinuous at c if and only if lim⁡x→c−f(x)<lim⁡x→c+f(x) (A monotone function on an interval has no discontinuity of the second kind: at every point both relevant one-sided limits exist, and an interior point c is a discontinuity exactly when lim⁡x→c−f(x)<lim⁡x→c+f(x)).

[L3]

Q≈N (Q is countably infinite) and the map q↦q^ embeds Q in R injectively (The rationals embed densely in the reals), so composing a bijection N→Q with that embedding gives a bijection e:N→QR onto the canonical copy of the rationals inside R; and strictly between any two distinct reals there lies a point of QR (The rationals embed densely in the reals, Equinumerous sets, A≈B and A⪯B, Injection, surjection, bijection).

[L4]

Every nonempty subset of N has a least element (The well-ordering principle).

[L5]

Proof

technique · direct
1.1

It is enough to treat a nondecreasing f: if f is nonincreasing then −f is nondecreasing and has the same discontinuity set, so the conclusion for −f is the conclusion for f. Assume from here on that f is nondecreasing.

L6
1.2

Fix once and for all a bijection e:N→QR; everything below is defined in terms of f, I and this one function.

L3choose
1.3

Call c∈I interior when both I− and I+ are nonempty, and write D0 for the set of interior points of I at which f is discontinuous. A point of I that is not interior has I−=∅, and is then a least element of I, or I+=∅, and is then a greatest element of I; a subset of R has at most one least and at most one greatest element, so D∖D0 has at most two elements.

A1
2.1

For c∈D0 put L−(c):=lim⁡x→c−f(x) and L+(c):=lim⁡x→c+f(x), both of which exist, and note L−(c)<L+(c).

step 1.3L1L2
2.2

Let c,c′∈D0 with c<c′. Take t:=e(k) for the least k with c<e(k)<c′, which exists because a point of QR lies strictly between c and c′; then t∈I, since c,c′∈I and I is order-convex.

step 1.3A1L3L4
3.1

For c∈D0 the set K(c):={ k∈N:L−(c)<e(k)<L+(c) } is nonempty, since a point of QR lies strictly between the two distinct reals L−(c) and L+(c) and e is onto QR; so j(c):=min⁡K(c) is a well-defined natural number, determined by c, f and e alone.

step 2.1L3L4
3.2

With c<t<c′ as in step 2.2: L+(c)=inf⁡{f(x):x∈I,x>c}≤f(t) because t is one of the points in that set, and f(t)≤sup⁡{f(x):x∈I,x<c′}=L−(c′) for the same reason on the other side. Hence L+(c)≤L−(c′).

step 2.2L1
4.1

The two open intervals (L−(c),L+(c)) and (L−(c′),L+(c′)) are therefore disjoint, so no point of QR lies in both, so e(j(c))≠e(j(c′)) and hence j(c)≠j(c′). Since c<c′ was an arbitrary pair of distinct elements of D0, the map j:D0→N is injective.

step 3.1step 3.2
5.1

Define J:D→N by J(c):=2 j(c)+1 for c∈D0; J(c):=0 if c∈D∖D0 is a least element of I; and J(c):=2 if c∈D∖D0 is a greatest element of I and not a least one. Then J is injective: it is injective on D0 by step 4.1, it separates the at most two points of D∖D0 from each other, and its values on D0 are odd while its values off D0 are even.

step 1.3step 4.1construct
6.1

Consequently J is a bijection from D onto the subset J[D]⊆N, which is at most countable; countability transfers along that bijection, so D is at most countable.

step 5.1L5∎

Remarks

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Converse to Froda: for every at most countable E⊆R there is a bounded nondecreasing f:R→R whose set of discontinuities is exactly E, every one of them a jump

Statement

Let E⊆R be at most countable (Finite, countably infinite, countable, uncountable). Then there is a function f:R→R such that

  1. f is nondecreasing (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences) and 0≤f(x)≤1 for every real x, so f is bounded (Lower bound, bounded below, bounded set);
  2. f is continuous at every x∉E and discontinuous at every x∈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), so the discontinuity set of f is exactly E;
  3. every discontinuity of f is a jump (Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind), with lim⁡x→c−f(x)=f(c)<lim⁡x→c+f(x) at every c∈E.

Together with Froda's theorem: the set of discontinuities of a monotone function on an interval is at most countable, the injection into N being built from one fixed enumeration of the rationals by least index, so no choice principle is used this settles the question completely: the sets that occur as discontinuity sets of monotone functions on R are exactly the at most countable ones.

The construction. For E=∅ take f:=0. Otherwise fix a surjection s:N→E (A nonempty set is at most countable iff it is a surjective image of N) and set

f(x)  :=  ∑k=0∞ak(x),ak(x):={1/2 k+1if s(k)<x,0otherwise,

(Series, partial sums, convergence and the sum, divergence, and the tail series, Integer powers am): the mass 1/2 k+1 is placed at the point s(k) and is collected by f strictly to the right of it. Repetitions in the enumeration are harmless; they only make the jump at a point larger.

Facts & Assumptions

Given: An at most countable E⊆R.

[L1]

A nonempty at most countable set is the image of a surjection s:N→E (A nonempty set is at most countable iff it is a surjective image of N, Finite, countably infinite, countable, uncountable).

[L2]

A series of nonnegative terms converges if and only if its partial sums are bounded above, and its sum is then the supremum of its partial sums; in particular every partial sum is at most the sum (A series of nonnegative terms converges iff its partial sums are bounded, and then the sum is their supremum, Series, partial sums, convergence and the sum, divergence, and the tail series, Lower bound, bounded below, bounded set).

[L3]

Finite sums: ∑k<n is monotone in the terms, splits as ∑k<n=∑k<m+∑k=mn−1 for m≤n, scales, and telescopes as ∑k<n(ck+1−ck)=cn−c0 (Laws of finite sums and finite products, Finite sums and finite products, by recursion).

[L4]

∑k≥0rk converges to 1/(1−r) for ∣r∣<1, the first term being r0=1 (For ∣r∣<1, ∑k≥0rk=1/(1−r), and for ∣r∣≥1 the series diverges, Integer powers am); a series converges if and only if each of its tails does, and ∑k≥0uk=∑k<Nuk+∑k≥Nuk (A series converges iff each of its tail series converges, and the sum splits as sN plus the N-th tail); a convergent sequence of reals comes within every positive ε of its limit from some index on (Limits and Cauchy sequences of reals).

[L5]

A nonempty finite set of reals, presented as {c0,…,cm}, has a maximum and a minimum (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set); and strictly between any two distinct reals there lies a real (The rationals embed densely in the reals).

Proof

technique · constructive
1.1

If E=∅, the constant function 0 is nondecreasing, takes values in [0,1], is continuous at every real, and has empty discontinuity set; all three claims hold vacuously for claim 3. Assume from here on that E≠∅ and fix a surjection s:N→E.

L1construct
1.2

For every n∈N, ∑k<n1/2 k+1=1−1/2 n: each term is 1/2 k+1=1/2 k−1/2 k+1, so the sum telescopes to 1/2 0−1/2 n=1−1/2 n.

L3
2.1

Define ak(x):=1/2 k+1 when s(k)<x and ak(x):=0 otherwise, and note 0≤ak(x)≤1/2 k+1 for every k and every real x.

step 1.1construct
2.2

For every real ε>0 there is n∈N with 1/2 n<ε: the partial sums tn:=∑k<n1/2 k converge to 2, and tn=2−2/2 n by the same telescoping as in step 1.2, so ∣tn−2∣=2/2 n<ε for all large n, whence 1/2 n<ε/2<ε for those n. Consequently the partial sums 1−1/2 n of ∑k1/2 k+1 have supremum 1, so that series converges with sum 1.

step 1.2L2L3L4
3.1

For every real x the series ∑kak(x) converges and 0≤f(x)≤1: its terms are nonnegative and its partial sums satisfy ∑k<nak(x)≤∑k<n1/2 k+1=1−1/2 n≤1, so they are bounded above by 1 and the sum, being their supremum, lies in [0,1].

step 2.1step 1.2L2L3
3.2

Left continuity holds at every real c: given real ε>0 take n with 1/2 n<ε; let F:={ k<n:s(k)<c }; if F=∅ put x0:=c−1, and otherwise put x0 to be a real with max⁡{s(k):k∈F}<x0<c, which exists because the maximum of the nonempty finite set {s(k):k∈F} is a real strictly below c.

step 2.2L5
3.3

Right continuity holds at every c∉E: given real ε>0 take n with 1/2 n<ε; since c∉E and s has image E, no k has s(k)=c, so every k<n has s(k)<c or s(k)>c. Let G:={ k<n:s(k)>c }; if G=∅ put y0:=c+1, and otherwise put y0 to be a real with c<y0<min⁡{s(k):k∈G}.

step 1.1step 2.2L5
4.1

f is nondecreasing: if x≤y then s(k)<x implies s(k)<y, so ak(x)≤ak(y) for every k, hence ∑k<nak(x)≤∑k<nak(y) for every n, and taking suprema gives f(x)≤f(y).

step 2.1step 3.1L2L3
4.2

For all reals x≤y and every n∈N with ak(x)=ak(y) for every k<n, one has f(y)−f(x)≤1/2 n: for N≥n the splitting ∑k<Nak(y)=∑k<nak(y)+∑k=nN−1ak(y)≤∑k<nak(x)+∑k=nN−11/2 k+1 holds, the last sum being at most ∑k≥n1/2 k+1=1−(1−1/2 n)=1/2 n; so every partial sum of ∑kak(y) is at most f(x)+1/2 n, and so is their supremum f(y).

step 2.1step 1.2step 3.1L2L3L4
4.3

Let c∈E and fix k0 with s(k0)=c. For every y>c and every N>k0 the finite sum ∑k<Nak(y) exceeds ∑k<Nak(c) by at least 1/2 k0+1, because the list k↦ak(y)−ak(c) has nonnegative entries, so the finite sum of its first N entries is at least its entry at the index k0, which is ak0(y)−ak0(c)=1/2 k0+1−0. Hence f(y)−1/2 k0+1≥∑k<Nak(c) for every N, the case N≤k0 holding because the partial sums of a nonnegative series are nondecreasing; so f(y)−1/2 k0+1 is an upper bound of those partial sums and therefore at least their supremum f(c).

step 1.1step 2.1step 3.1L2L3
5.1

With x0 as in step 3.2 and any x with x0<x≤c: for k<n with s(k)<c we have s(k)≤max⁡{s(j):j∈F}<x0<x, so ak(x)=1/2 k+1=ak(c); and for k<n with s(k)≥c≥x we have ak(x)=0=ak(c). So ak(x)=ak(c) for every k<n, and step 4.2 applied to the pair x≤c gives 0≤f(c)−f(x)≤1/2 n<ε.

step 2.1step 4.1step 4.2step 3.2
5.2

With y0 as in step 3.3 and any y with c≤y<y0: for k<n with s(k)<c≤y we get ak(y)=1/2 k+1=ak(c), and for k<n with s(k)>c we have s(k)≥min⁡{s(j):j∈G}>y0>y, so ak(y)=0=ak(c). So ak(y)=ak(c) for every k<n, and step 4.2 applied to the pair c≤y gives 0≤f(y)−f(c)≤1/2 n<ε.

step 2.1step 4.1step 4.2step 3.3
5.3

So f is discontinuous at c: for ε:=1/2 k0+1>0 and any real δ>0 the point y:=c+δ/2 satisfies ∣y−c∣<δ and ∣f(y)−f(c)∣≥ε, so no δ witnesses the continuity condition at c.

step 4.3
6.1

Hence f is continuous at every c∉E: fix a real ε>0, take x0 as in step 3.2 and y0 as in step 3.3 for that same ε, and put δ:=min⁡{c−x0,y0−c}>0; then every real x with ∣x−c∣<δ satisfies x0<x<y0 and therefore ∣f(x)−f(c)∣<ε, by step 5.1 when x≤c and by step 5.2 when x≥c.

step 5.1step 5.2L5
6.2

Every point of E is an interior point of the order-convex set R, so both one-sided limits of f exist there; step 5.1 gives lim⁡x→c−f(x)=f(c) and step 4.3 gives lim⁡x→c+f(x)≥f(c)+1/2 k0+1>f(c). The two one-sided limits therefore differ, and the discontinuity at c is a jump.

step 5.1step 4.3step 5.3L6
7.1

Claims 1, 2 and 3 hold for the function f constructed in steps 1.1 and 2.1: claim 1 by steps 3.1 and 4.1, claim 2 by steps 6.1 and 5.3, and claim 3 by step 6.2.

step 3.1step 4.1step 6.1step 5.3step 6.2discharge-construct∎

Remarks

  • Why the mass is collected strictly to the right. The definition uses s(k)<x rather than s(k)≤x, and that is what makes f left continuous everywhere, as steps 3.2 and 5.1 show without any hypothesis on c. The value f(c) at a point of E is therefore the left limit, and the whole jump sits on the right. Using s(k)≤x would produce a right continuous function with the same discontinuity set; nothing else would change.

  • Repetitions in the enumeration are harmless. If s takes the value c at several indices, the jump at c is the total mass ∑{1/2 k+1:s(k)=c} rather than a single term. Step 4.3 uses only one index k0 and so needs no such sum; it establishes a lower bound for the jump, which is all that discontinuity requires.

  • Boundedness is free, and it is worth recording. The total mass available is ∑k≥01/2 k+1=1, so f maps R into [0,1] however large E is. A bounded nondecreasing function on R can therefore have a dense set of discontinuities; the companion page takes E=Q and gets exactly that.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

A continuous injective function on an interval is strictly monotone

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and let f:I→R be 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) and injective (Injection, surjection, bijection). Then f is strictly monotone (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences): either f(x)<f(y) whenever x<y in I, or f(x)>f(y) whenever x<y in I.

Both hypotheses are needed and neither can be weakened to the other. Continuity alone does not give injectivity, and injectivity alone does not give monotonicity: the companion page exhibits a continuous injection on [0,1]∪[2,3], a set that is not order-convex, that is not monotone. So it is order-convexity of the domain, and not merely continuity, that forces the conclusion.

Facts & Assumptions

Given: An order-convex I⊆R and a continuous injective f:I→R.

[A1]

I is order-convex: x,y∈I and x≤z≤y imply z∈I (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[A2]

f is injective: f(u)=f(v) implies u=v (Injection, surjection, bijection).

[A3]

f is continuous at every point of I; the restriction of f to a subset S⊆I is continuous at every point of S, since the ε-δ condition 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 quantifies over fewer points when the domain shrinks.

[L1]

Intermediate value theorem: if u≤v, g:[u,v]→R is continuous and y lies between g(u) and g(v) in either order, then g(p)=y for some p∈[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]

Strictly between any two distinct reals there lies a real (The rationals embed densely in the reals).

[L3]

f is increasing when f(x)<f(y) for all x<y in I, decreasing when f(x)>f(y) for all x<y in I, and strictly monotone when it is one or the other (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences).

Proof

technique · contradiction
1.1

Suppose, for contradiction, that f is not strictly monotone: f is not increasing and f is not decreasing.

assume-contra
1.2

Three-point claim. For all u<v<w in I, either f(u)<f(v)<f(w) or f(u)>f(v)>f(w). Suppose not. By injectivity the three values are pairwise distinct, so the failure means that f(v) is not between f(u) and f(w); hence either f(v)>f(u) and f(v)>f(w), or f(v)<f(u) and f(v)<f(w).

A2
2.1

Being decreasing means f(x)>f(y) for all x<y in I, so its failure gives a,b∈I with a<b and not f(a)>f(b), that is f(a)≤f(b); injectivity together with a≠b gives f(a)≠f(b), so f(a)<f(b).

step 1.1A2L3
2.2

In the first case of step 1.2 pick a real y with max⁡{f(u),f(w)}<y<f(v); in the second pick y with f(v)<y<min⁡{f(u),f(w)}. Such a y exists because the two bounds are distinct reals.

step 1.2L2
3.1

With y as in step 2.2, [u,v]⊆I and [v,w]⊆I by order-convexity, and f restricted to each is continuous; y lies strictly between f(u) and f(v), and strictly between f(v) and f(w). So there are p∈[u,v] and q∈[v,w] with f(p)=y=f(q).

step 2.2A1A3L1
4.1

Since f(p)=y≠f(v) and f(q)=y≠f(v) we have p≠v≠q, so u≤p<v<q≤w and in particular p≠q; but f(p)=f(q) contradicts injectivity. The three-point claim of step 1.2 is therefore established.

step 1.2step 3.1A2
5.1

Let x∈I with x<a. Applying the three-point claim to x<a<b gives f(x)<f(a)<f(b) or f(x)>f(a)>f(b); the second is impossible because f(a)<f(b). So f(x)<f(a).

step 2.1step 4.1
6.1

Let x∈I with x>a. If x<b, the three-point claim applied to a<x<b gives f(a)<f(x)<f(b), the alternative being impossible as in step 5.1; if x=b then f(a)<f(x) by step 2.1; and if x>b, the claim applied to a<b<x gives f(a)<f(b)<f(x). In every case f(x)>f(a).

step 2.1step 4.1
6.2

Let c,d∈I with c<d≤a; we show f(c)<f(d). If d=a then c<a and step 5.1 gives f(c)<f(a)=f(d). If d<a then the three-point claim applied to c<d<a gives f(c)<f(d)<f(a) or f(c)>f(d)>f(a), and the second contradicts f(d)<f(a) from step 5.1; so f(c)<f(d).

step 4.1step 5.1
7.1

Let c,d∈I with a≤c<d; we show f(c)<f(d). If c=a then d>a and step 6.1 gives f(d)>f(a)=f(c). If a<c then the three-point claim applied to a<c<d gives f(a)<f(c)<f(d) or f(a)>f(c)>f(d), and the second contradicts f(c)>f(a) from step 6.1; so f(c)<f(d).

step 4.1step 6.1
7.2

The only remaining case is c<a<d, where steps 5.1 and 6.1 give f(c)<f(a)<f(d) directly.

step 5.1step 6.1
8.1

Steps 7.1, 6.2 and 7.2 cover every pair c<d in I: either a≤c, which is step 7.1, or c<a, and then d≤a, which is step 6.2, or a<d, which is step 7.2. So f(x)<f(y) whenever x<y in I, that is, f is increasing. This contradicts step 1.1, which assumed that f is not increasing; the assumption of step 1.1 is therefore false and f is strictly monotone.

step 1.1step 7.1step 6.2step 7.2L3discharge-contradiction∎

Remarks

  • The three-point claim is the whole content. Steps 1.2, 2.2, 3.1 and 4.1 say that a continuous injection on an interval cannot fold: the middle of three points always has the middle value. Everything after that is bookkeeping, comparing an arbitrary pair with one fixed pair a<b on which the direction is known.

  • Where the intermediate value theorem enters. Once only, in step 3.1, and it is what makes order-convexity of I indispensable: the segments [u,v] and [v,w] must lie inside the domain for the theorem to apply. That is exactly the hypothesis the companion page's counterexample removes.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Continuous inverse theorem: a continuous injective f on an interval I is a bijection onto the order-convex set f[I], and the inverse g:f[I]→I is continuous and strictly monotone in the same sense as f

Statement

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and let f:I→R be 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) and injective (Injection, surjection, bijection). Then:

  1. f is strictly monotone (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences);
  2. f[I] is order-convex;
  3. the map f:I→f[I] is a bijection, so there is exactly one g:f[I]→I with g(f(x))=x for every x∈I and f(g(u))=u for every u∈f[I];
  4. g is strictly monotone in the same sense as f: increasing if f is increasing, decreasing if f is decreasing;
  5. g is continuous on f[I].

"Interval" means "order-convex" here, as throughout this library (A subset of R is connected if and only if it is order-convex, that is, an interval is what licenses the word and Intervals of R: the nine order-convex forms, nondegeneracy, and length records that the classification of order-convex sets into the nine written forms is not proved here). No compactness and no boundedness is assumed: I may be open, half-open, unbounded, or a single point.

Facts & Assumptions

Given: An order-convex I⊆R and a continuous injective f:I→R.

[L1]

A continuous injective function on an order-convex subset of R is strictly monotone (A continuous injective function on an interval is strictly monotone).

[L2]
[L3]

If J⊆R is order-convex, h:J→R satisfies h(u)≤h(v) whenever u,v∈J and u≤v, and h[J] is order-convex, then h is continuous on J (A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous).

[L5]

f is injective, so f:I→f[I] is a bijection and has a unique two-sided inverse (Injection, surjection, bijection).

[L6]

f increasing means f(x)<f(y) whenever x<y in I; −f is decreasing exactly when f is increasing, and −S is order-convex exactly when S is (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences, Intervals of R: the nine order-convex forms, nondegeneracy, and length).

Proof

technique · direct
1.1

Claim 1 is immediate: f is continuous and injective on the order-convex set I, hence strictly monotone.

L1
1.2

Claim 2 is immediate: I is order-convex and f is continuous on I, so f[I] is order-convex.

L2
1.3

Claim 3 is immediate: f is injective and f:I→f[I] is onto its image by definition of the image, so it is a bijection and has a unique two-sided inverse g:f[I]→I.

L5
2.1

Suppose f is increasing, and let u,v∈f[I] with u<v. Write u=f(p) and v=f(q) with p=g(u) and q=g(v) in I. If q≤p then f(q)≤f(p), since q=p gives equality and q<p gives f(q)<f(p); that is v≤u, contradicting u<v. Hence p<q, that is g(u)<g(v), and g is increasing.

step 1.1step 1.3L6
2.2

Suppose instead that f is decreasing, and put F:=−f, that is F(x):=−f(x). Then F is continuous on I, it is injective because f is, and it is increasing.

step 1.1L4L6
3.1

Still with f increasing: g satisfies g(u)≤g(v) whenever u≤v in f[I], by step 2.1 when u<v and trivially when u=v; the domain f[I] is order-convex by step 1.2; and the image g[f[I]] is I, which is order-convex, because g is onto I. So the monotone-with-interval-image criterion applies and g is continuous on f[I].

step 1.2step 1.3step 2.1L3
4.1

By steps 2.1 and 3.1 applied to F, the inverse G:F[I]→I of F is increasing and continuous, and F[I]=−f[I] is order-convex.

step 2.1step 3.1step 2.2
5.1

For u∈f[I] one has −u∈F[I] and G(−u)=g(u), since F(g(u))=−f(g(u))=−u and G is the inverse of F. So g is the composite of the continuous map u↦−u from f[I] into F[I] with the continuous G, hence continuous on f[I].

step 1.3step 4.1L4
6.1

In that case g is decreasing: for u<v in f[I] one has −v<−u in F[I], so G(−v)<G(−u) because G is increasing, that is g(v)<g(u).

step 4.1step 5.1
7.1

Claims 4 and 5 are now proved in both cases: for f increasing by steps 2.1 and 3.1, and for f decreasing by steps 5.1 and 6.1; and by step 1.1 there is no other case.

step 1.1step 2.1step 3.1step 5.1step 6.1∎

Remarks

  • No epsilon-delta argument appears anywhere. Continuity of the inverse is obtained entirely from A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous, whose hypotheses are exactly the two facts the theorem has already established: the inverse is monotone, and its image is the order-convex set I. The decreasing case is reduced to the increasing one by composing with u↦−u rather than repeating the argument.

  • What the theorem is used for. It is the tool that turns a strictly monotone continuous bijection into a continuous one in the other direction, and the standard elementary functions are built with it: the companion page derives the continuity of x↦x1/n this way.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

The Cantor function is continuous on [0,1]

Statement

Facts & Assumptions

[L3]

If J⊆R is order-convex, h:J→R satisfies h(u)≤h(v) whenever u,v∈J and u≤v, and h[J] is order-convex, then h is continuous on J (A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous).

[L4]

Every interval of the nine written forms, and in particular [0,1], is order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

Proof

technique · direct
1.1

The domain [0,1] is order-convex.

L4
1.2

c satisfies c(x)≤c(y) whenever x,y∈[0,1] and x≤y.

L1
1.3

The image c[ [0,1] ] is exactly [0,1], since c is surjective onto [0,1], and [0,1] is order-convex.

L2L4
2.1

The three hypotheses of the monotone-with-interval-image criterion hold for c on [0,1], so c is continuous on [0,1].

step 1.1step 1.2step 1.3L3
3.1

c is nondecreasing, which is what the inequality of step 1.2 says, and c(0)=0 and c(1)=1.

step 1.2L2L5∎

Remarks

RemarkRemark: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

The Cantor function is continuous and nondecreasing, climbs from 0 to 1, and is constant on every interval removed in the construction of the Cantor set, so all of its increase happens on a set of measure zero

Remark

Collect what is now known about the Cantor function c:[0,1]→R (The Cantor function on [0,1], defined on the Cantor set through ternary digits and extended constantly across each removed interval) and the Cantor set C (The Cantor middle-thirds set as the intersection of the sets Cn obtained by removing open middle thirds).

All of the increase happens on C, in the following exact sense. Let x<y in [0,1] with c(x)<c(y). Then (x,y)∩C≠∅. Indeed, suppose (x,y)∩C=∅ and pick any t with x<t<y. Then t∉C, so t lies in the open interval (u,v) of a pair u<v of points of C with (u,v)∩C=∅, and c is constant on [u,v]. Now u<t<y, and u∈C, so u∉(x,y) and therefore u≤x; symmetrically x<t<v and v∈C give v≥y. Hence [x,y]⊆[u,v] and c(x)=c(y), contrary to assumption. So a nondegenerate interval on which c actually rises must meet C, a set of measure zero, while on the complement of C the function is locally constant.

What is not claimed here. Nothing above says that c is differentiable anywhere, that its derivative vanishes anywhere, or that c is singular: no notion of derivative is available at this point in the reading order, and no notion of Lebesgue measure is developed in the library as it stands. Measure zero here is exactly Measure zero (a countable cover by intervals of total length below every ε) and content zero (a finite such cover), a condition on covers by intervals, and every statement above is a statement about c, about C, and about that covering condition, and about nothing else.

Why this is worth recording at all. A continuous nondecreasing function that climbs from 0 to 1 might be expected to do its climbing on a set that is large in some sense; c does all of it on a set that is null and, being nowhere dense (The Cantor set is compact, perfect, uncountable, nowhere dense and of measure zero, and it contains no interval of positive length, so its only nonempty connected subsets are single points, claim 5), small in category as well. The companion page pushes the same observation one step further: c maps the null set C onto the whole of [0,1].

DefinitionDefinition: AI-adaptedProof: Not applicableverified 2026-08-09 (gpt-5.6-terra-codex-subscription)Open item page →

The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals

Definition

Let A⊆R and let f:A→R. All suprema and infima below are taken in the extended real line R‾=R∪{−∞,+∞} (The extended real line R‾=R∪{−∞,+∞}, its order, and the arithmetic that is left undefined), where every subset has a least upper bound and a greatest lower bound (Every subset of R‾ has a least upper bound and a greatest lower bound in R‾, agreeing with the real supremum and infimum on nonempty sets bounded in R); no boundedness hypothesis on f is therefore needed anywhere, and none is imposed.

Oscillation on a set. For S⊆A put

ωf(S)  :=  sup⁡{ ∣f(x)−f(y)∣  :  x,y∈S }  ∈  R‾.

Oscillation at a point. For c∈A put

ωf(c)  :=  inf⁡{ ωf(A∩Nδ(c))  :  δ∈R, δ>0 }  ∈  R‾,

where Nδ(c)=(c−δ,c+δ) is the δ-neighbourhood of c (The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

The two uses of the symbol ωf are distinguished by their argument: a subset of A in the first, a point of A in the second. Where confusion is possible the first is written ωf(S) with S named as a set.

Both values are well posed; point oscillation and nonempty-set oscillation are nonnegative

The set in the first display is nonempty whenever S is, since x=y∈S gives the value ∣f(x)−f(x)∣=0; so ωf(S)≥0 for nonempty S, and ωf(S)=sup⁡∅=−∞ for S=∅ (Every subset of R‾ has a least upper bound and a greatest lower bound in R‾, agreeing with the real supremum and infimum on nonempty sets bounded in R). Only nonempty S occurs below.

The set in the second display is nonempty, since some real δ>0 exists, and each of its members is ≥0: for c∈A the set A∩Nδ(c) contains c itself, because ∣c−c∣=0<δ, so it is nonempty and ωf(A∩Nδ(c))≥0 (Basic properties of the absolute value). Hence 0 is a lower bound of that set and

0  ≤  ωf(c)  ≤  ωf(A∩Nδ(c))for every real δ>0,

the second inequality because ωf(c) is a lower bound of the set of which ωf(A∩Nδ(c)) is a member. In particular ωf(c) is never −∞.

Monotonicity, and the case of a bounded f

ωf is monotone under inclusion. If S⊆T⊆A then every value ∣f(x)−f(y)∣ with x,y∈S is also a value with x,y∈T, so the first set of values is contained in the second and ωf(S)≤ωf(T): a supremum of a subset is at most the supremum of the set. Consequently δ↦ωf(A∩Nδ(c)) is nondecreasing in δ, since δ≤δ′ gives Nδ(c)⊆Nδ′(c) (The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

When f is bounded, nonempty-set and point oscillations are real. Suppose there is a real M with ∣f(x)∣≤M for every x∈A (Lower bound, bounded below, bounded set). Then for x,y∈A,

∣f(x)−f(y)∣  ≤  ∣f(x)∣+∣f(y)∣  ≤  2M

(The triangle inequality, Basic properties of the absolute value), so ωf(S)≤2M for every S⊆A. If S is nonempty, ωf(S) is a real number in [0,2M], and every point oscillation is also a real number in [0,2M]: the supremum of a nonempty subset of R that is bounded above in R is the real supremum (Every subset of R‾ has a least upper bound and a greatest lower bound in R‾, agreeing with the real supremum and infimum on nonempty sets bounded in R, Complete ordered field (least-upper-bound property), Greatest lower bound (infimum)). The convention ωf(∅)=−∞ remains the single empty-set exception. Apart from that exception, an infinite extended value can occur only when f is unbounded.

The notation. The letter is ω throughout this library, never "osc⁡", and the function is always in the subscript.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

f:A→R is continuous at c∈A if and only if ωf(c)=0

Statement

Let A⊆R, let f:A→R and let c∈A. Then

f is continuous at c⟺ωf(c)=0

(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 oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals).

Since ωf(c)≥0 always (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals), the equivalent form of the right-hand side is: for every real ε>0 there is a real δ>0 with ωf(A∩Nδ(c))<ε.

This is the tool that converts a pointwise condition into a set condition. Continuity at c is a statement about f near c with a quantifier over ε; ωf(c)=0 is the vanishing of a single extended real attached to the point. The change of form is what makes the discontinuity set accessible: the sets { x:ωf(x)≥ε } are closed (For every real ε>0 the set { x∈A:ωf(x)≥ε } is the intersection with A of a closed subset of R; in particular it is closed in R when A=R) and their union over ε=1,1/2,1/3,… is the discontinuity set (For f:A→R the set of points of A at which f is discontinuous is the intersection with A of an Fσ subset of R, and the set of points at which f is continuous is the intersection with A of a Gδ subset; for A=R the two sets are Fσ and Gδ outright).

Facts & Assumptions

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

[L1]

f is continuous at c exactly when for every real ε>0 there is a real δ>0 with ∣f(x)−f(c)∣<ε for every x∈A with ∣x−c∣<δ; equivalently for every x∈A∩Nδ(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]

ωf(S)=sup⁡{∣f(x)−f(y)∣:x,y∈S} and ωf(c)=inf⁡{ωf(A∩Nδ(c)):δ>0}, both in R‾; 0≤ωf(c)≤ωf(A∩Nδ(c)) for every real δ>0, and c∈A∩Nδ(c) (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals, The extended real line R‾=R∪{−∞,+∞}, its order, and the arithmetic that is left undefined).

[L3]

In R‾ every subset has a least upper bound and a greatest lower bound; a supremum is at most an extended real u exactly when u bounds every member of the set, and an infimum is at least an extended real ℓ exactly when ℓ bounds every member from below (Every subset of R‾ has a least upper bound and a greatest lower bound in R‾, agreeing with the real supremum and infimum on nonempty sets bounded in R).

[L4]

∣u−w∣≤∣u−v∣+∣v−w∣ and ∣u∣≥0 for reals u,v,w (Basic properties of the absolute value).

Proof

technique · direct
1.1

Suppose f is continuous at c and let ε>0 be real. Take δ>0 with ∣f(x)−f(c)∣<ε/2 for every x∈A∩Nδ(c).

L1
1.2

Conversely, suppose ωf(c)=0 and let ε>0 be real. Not every member of {ωf(A∩Nδ(c)):δ>0} can be ≥ε, for then ε would be a lower bound of that set and the infimum ωf(c)=0 would satisfy 0≥ε. So there is a real δ>0 with ωf(A∩Nδ(c))<ε.

L2L3
2.1

For x,y∈A∩Nδ(c) with δ as in step 1.1, ∣f(x)−f(y)∣≤∣f(x)−f(c)∣+∣f(c)−f(y)∣<ε/2+ε/2=ε; so ε is an upper bound of the set whose supremum is ωf(A∩Nδ(c)), and therefore ωf(A∩Nδ(c))≤ε.

step 1.1L2L3L4
2.2

With δ as in step 1.2 and any x∈A∩Nδ(c): both x and c lie in A∩Nδ(c), so ∣f(x)−f(c)∣ is one of the values whose supremum is ωf(A∩Nδ(c)) and therefore ∣f(x)−f(c)∣≤ωf(A∩Nδ(c))<ε.

step 1.2L2L3
3.1

Hence 0≤ωf(c)≤ε for every real ε>0. If ωf(c) were not 0 it would satisfy 0<ωf(c)≤1, hence be a positive real, and taking ε:=ωf(c)/2 would give ωf(c)≤ωf(c)/2, which is false for a positive real. So ωf(c)=0.

step 2.1L2L3
4.1

Since ε>0 was arbitrary in step 1.2, the continuity condition holds at c, and f is continuous at c. Together with step 3.1 this proves the equivalence.

step 3.1step 2.2L1∎

Remarks

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

For every real ε>0 the set { x∈A:ωf(x)≥ε } is the intersection with A of a closed subset of R; in particular it is closed in R when A=R

Statement

Let A⊆R, let f:A→R and let ε∈R with ε>0. Put

Eε  :=  { x∈A:ωf(x)≥ε }

(The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals). Then there is a closed G⊆R (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen) with

Eε  =  A∩G.

In particular, if A=R then Eε is itself a closed subset of R.

The set G is produced explicitly and does not depend on any choice: it is the complement of

U  :=  { y∈R:ωf(A∩Nρ(y))<ε  for some real ρ>0 },

which the proof shows to be open. Note that y ranges over all of R here and not only over A; the expression ωf(A∩Nρ(y)) is the oscillation of f on a subset of A and makes sense for every real y, taking the value sup⁡∅=−∞ when A∩Nρ(y)=∅ (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals, Every subset of R‾ has a least upper bound and a greatest lower bound in R‾, agreeing with the real supremum and infimum on nonempty sets bounded in R).

Facts & Assumptions

Given: A⊆R, a function f:A→R, and a real ε>0.

[L1]

ωf(S)=sup⁡{∣f(x)−f(y)∣:x,y∈S} in R‾, and ωf(S)≤ωf(T) whenever S⊆T⊆A; for c∈A, ωf(c)=inf⁡{ωf(A∩Nδ(c)):δ>0} (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals, The extended real line R‾=R∪{−∞,+∞}, its order, and the arithmetic that is left undefined).

[L2]

In R‾ every subset has a greatest lower bound; an infimum is ≥ an extended real ℓ exactly when ℓ bounds the set from below, and the infimum is ≤ every member of the set (Every subset of R‾ has a least upper bound and a greatest lower bound in R‾, agreeing with the real supremum and infimum on nonempty sets bounded in R).

[L3]

Nδ(x)={y:∣y−x∣<δ}; if ∣y−x∣<ρ/2 then Nρ/2(y)⊆Nρ(x), since ∣z−y∣<ρ/2 gives ∣z−x∣≤∣z−y∣+∣y−x∣<ρ (The ε-neighbourhood and the punctured ε-neighbourhood of a point of R).

[L4]

U⊆R is open when every point of U has a neighbourhood contained in U, and G⊆R is closed exactly when R∖G is open (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen).

Proof

technique · direct
1.1

Define U:={ y∈R:ωf(A∩Nρ(y))<ε for some real ρ>0 } and G:=R∖U.

construct
2.1

U is open. Let y∈U with witness ρ>0, and let z∈Nρ/2(y). Then Nρ/2(z)⊆Nρ(y), hence A∩Nρ/2(z)⊆A∩Nρ(y), hence ωf(A∩Nρ/2(z))≤ωf(A∩Nρ(y))<ε, so z∈U with witness ρ/2. Thus Nρ/2(y)⊆U.

step 1.1L1L3L4
2.2

Let x∈A with x∉U. Then ωf(A∩Nδ(x))≥ε for every real δ>0, so ε is a lower bound of the set whose infimum is ωf(x), and therefore ωf(x)≥ε, that is x∈Eε.

step 1.1L1L2
2.3

Let x∈Eε, so x∈A and ωf(x)≥ε. For every real δ>0 the value ωf(A∩Nδ(x)) is at least the infimum ωf(x), hence at least ε; so no ρ witnesses membership of x in U, that is x∉U.

step 1.1L1L2
3.1

G is closed, being the complement of the open set U.

step 1.1step 2.1L4
4.1

Steps 2.2 and 2.3 together say that for x∈A one has x∈Eε if and only if x∈G; hence Eε=A∩G with G closed.

step 3.1step 2.2step 2.3
5.1

If A=R then Eε=R∩G=G is closed in R.

step 4.1L4∎

Remarks

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passverified 2026-08-27 (gpt-5)Open item page →

For f:A→R the set of points of A at which f is discontinuous is the intersection with A of an Fσ subset of R, and the set of points at which f is continuous is the intersection with A of a Gδ subset; for A=R the two sets are Fσ and Gδ outright

Statement

Let A⊆R and let f:A→R. Write

D  :=  { x∈A:f is discontinuous at x },C  :=  A∖D

(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, Discontinuity of f at a point of its domain, and its classification: removable discontinuity, jump discontinuity and essential discontinuity, equivalently Rudin's discontinuities of the first and of the second kind). Then:

  1. Pointwise exhaustion. D={ x∈A:ωf(x)>0 } (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals), and D is the union of the increasing sequence of superlevel sets D  =  ⋃n∈N{ x∈A:ωf(x)≥1/ι(n+1) } (The canonical natural ι(n)=n⋅1F of a field), whose thresholds are 1,1/2,1/3,….
  2. Descriptive form. There is an Fσ set F⊆R and a Gδ set V⊆R (Fσ and Gδ subsets of R) with D  =  A∩F,C  =  A∩V,V=R∖F, and F may be taken to be ⋃n∈NGn with each Gn a closed subset of R cutting down on A to the n-th set of claim 1 (For every real ε>0 the set { x∈A:ωf(x)≥ε } is the intersection with A of a closed subset of R; in particular it is closed in R when A=R).

In particular, when A=R the discontinuity set D is an Fσ subset of R and the continuity set C is a Gδ subset, and claim 1 reads D=⋃n{ x∈R:ωf(x)≥1/ι(n+1) }.

Claim 1 is stated separately because it is what later arguments cite downstream. The exhaustion of D by the superlevel sets {ωf≥1/ι(n+1)} is exactly the form needed when a later proof establishes a property one threshold at a time, so the identity itself is recorded here and not only the descriptive conclusion of claim 2.

The statement is relative on purpose. For a general domain A the sets D and C are subsets of A, and neither is Fσ or Gδ in R in general; what the proof produces are two subsets of R that cut down to them. The absolute form is stated only for A=R, which is the case used later by the realization and exact-continuity-set examples.

Facts & Assumptions

Given: A⊆R and a function f:A→R.

[L2]
[L3]

For every real η>0 there is a natural m≥1 with 1/ι(m)<η, where ι(m) is the canonical natural of m in R; and ι is strictly increasing and positive on the naturals ≥1 (For every ε>0 in a complete ordered field there is a natural n≥1 with 1/n<ε, The canonical natural ι(n)=n⋅1F of a field, Canonical naturals are positive and strictly increasing).

[L4]

A subset of R is Fσ when it is the union of a sequence of closed sets and Gδ when it is the intersection of a sequence of open sets; S is Fσ if and only if R∖S is Gδ (Fσ and Gδ subsets of R, Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen).

Proof

technique · direct
1.1

For each n∈N put εn:=1/ι(n+1), a positive real since n+1≥1, and let Gn⊆R be closed with {x∈A:ωf(x)≥εn}=A∩Gn.

L2L3construct
1.2

D={ x∈A:ωf(x)>0 }: a point x∈A is a discontinuity exactly when ωf(x)≠0, and ωf(x)≥0 always, so exactly when ωf(x)>0.

L1
2.1

D⊆⋃n∈N(A∩Gn). Let x∈D, so ωf(x)>0. If ωf(x)≥ε0=1 then x∈A∩G0. Otherwise 0<ωf(x)<1, so ωf(x) is a positive real, and there is a natural m≥1 with 1/ι(m)<ωf(x); writing m=n+1 with n∈N gives ωf(x)>εn, hence x∈A∩Gn.

step 1.1step 1.2L3
2.2

Conversely ⋃n∈N(A∩Gn)⊆D: if x∈A∩Gn then ωf(x)≥εn>0, so x∈D.

step 1.1step 1.2L3
3.1

Put F:=⋃n∈NGn, an Fσ subset of R since each Gn is closed and the family is indexed by N. Then A∩F=⋃n(A∩Gn)=D.

step 1.1step 2.1step 2.2L4
3.2

Claim 1 is proved: D={x∈A:ωf(x)>0} by step 1.2, and D=⋃n∈N{x∈A:ωf(x)≥εn} by steps 2.1 and 2.2, since A∩Gn is by step 1.1 exactly the set {x∈A:ωf(x)≥εn} with εn=1/ι(n+1). The union is increasing, since n≤m gives ι(n+1)≤ι(m+1) and hence εm≤εn.

step 1.1step 1.2step 2.1step 2.2L3
4.1

Put V:=R∖F, a Gδ subset of R. Then A∩V=A∖(A∩F)=A∖D=C.

step 3.1L4
5.1

Claim 2 is proved by steps 3.1 and 4.1; and for A=R the two identities read D=F and C=V, so D is Fσ and C is Gδ outright.

step 3.1step 3.2step 4.1∎

Remarks

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

The Dirichlet function 1Q, and Thomae's function t with t(x)=1/q at a rational x=p/q in lowest terms with q≥1 and t(x)=0 at every irrational x

Definition

Throughout, N⊆Z⊆Q⊆R denotes the chain of canonical embeddings (The naturals embed in the integers, The integers embed in the rationals, The rationals embed densely in the reals), and each set is identified with its image in R, as elsewhere in this library; for a natural q the real ι(q)=q⋅1R is the canonical natural (The canonical natural ι(n)=n⋅1F of a field), and ι(q)>0 for q≥1 (Canonical naturals are positive and strictly increasing). A real is rational when it lies in Q and irrational otherwise; both sets are dense in R (Both Q and R∖Q are dense in R, and every nonempty open subset of R is uncountable).

The Dirichlet function

1Q:R→R,1Q(x):={1if x∈Q,0if x∉Q.

This is the indicator of the rationals. It is a function because every real either lies in Q or does not, and the two clauses are exclusive.

The least denominator of a rational

Let x∈Q and put

Q(x)  :=  { q∈N  :  q≥1  and  ι(q) x∈Z }.

Q(x) is nonempty. Every rational is a/b with a∈Z and b a positive integer (The integers embed in the rationals), and a positive integer is ι(q) for a unique natural q≥1 (The naturals embed in the integers); then ι(q) x=a∈Z, so q∈Q(x).

By the well-ordering principle (The well-ordering principle) the nonempty subset Q(x)⊆N has a least element. Write

q(x)  :=  min⁡Q(x)  ≥  1,

the least denominator of x, and p(x):=ι(q(x)) x∈Z, so that

x  =  p(x)ι(q(x)).

Nothing is selected here: q(x) is the least element of a set determined by x, so it is a function of x alone.

The least denominator is the denominator in lowest terms. The integers p(x) and q(x) are coprime (Coprime integers: gcd⁡(a,b)=1). Indeed put d:=gcd⁡(p(x),q(x)), which satisfies d≥1 because q(x)≥1 makes the pair different from (0,0) (gcd⁡ is symmetric and unchanged by signs: gcd⁡(a,b)=gcd⁡(b,a)=gcd⁡(∣a∣,∣b∣); moreover gcd⁡(a,0)=∣a∣, gcd⁡(a,1)=1, gcd⁡(a,a)=∣a∣, and gcd⁡(a,b)≥1 unless a=b=0, Common divisor, and the greatest common divisor gcd⁡(a,b), with the convention gcd⁡(0,0):=0). Then d divides q(x), so q(x)/d is a natural number ≥1, and ι(q(x)/d)=ι(q(x))/d because ι carries products of naturals to products (Canonical naturals are positive and strictly increasing); hence

ι(q(x)/d) x  =  ι(q(x)) xd  =  p(x)d  ∈  Z,

so q(x)/d∈Q(x) and therefore q(x)/d≥q(x), which forces d=1. Conversely, a lowest-terms denominator is the least one, so the description is unambiguous. Suppose x=p/ι(q) with q≥1 a natural, p∈Z and gcd⁡(p,q)=1. Then q∈Q(x), so q0:=q(x)≤q; and from p/ι(q)=p(x)/ι(q0) we get q0p=q p(x) in Z, so q∣q0p, and gcd⁡(p,q)=1 gives q∣q0 (If gcd⁡(a,b)=1 and a∣bc then a∣c; and if a∣c, b∣c and gcd⁡(a,b)=1 then ab∣c, claim 1), hence q≤q0. So q=q(x): writing x=p/q "in lowest terms with q≥1" and taking q=q(x) describe the same integer, and If d=gcd⁡(a,b) is nonzero then a/d and b/d are coprime is what produces such a representation from an arbitrary one.

Thomae's function

t:R→R,t(x):={1/ι(q(x))if x∈Q,0if x∉Q.

It is also called the popcorn function or the ruler function. The value is well defined because q(x) is, and ι(q(x))≥1>0 is invertible.

Boundary values, stated rather than left to the reader.

  • t(0)=1. Indeed ι(1)⋅0=0∈Z, so 1∈Q(0) and q(0)=1; the representation is 0=0/1.
  • t(m)=1 for every integer m, by the same computation with 1∈Q(m).
  • 0<t(x)≤1 for every rational x, since ι(q(x))≥1; and t(x)=0 exactly at the irrationals.

On the range. The values of t are 0 and the reciprocals 1/ι(q) of the canonical naturals q≥1; every such value is attained, 1/ι(q) being the value at the rational 1/ι(q) itself, whose least denominator is q because ι(k)/ι(q)∈Z with 1≤k<q would give a positive integer smaller than 1.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passverified 2026-08-27 (gpt-5)Open item page →

The Dirichlet function is continuous at no point of R, and Thomae's function is continuous at every irrational and at no rational, so its set of continuity points is exactly the set of irrationals and its oscillation at c equals t(c)

Statement

Let 1Q and t be the Dirichlet and Thomae functions (The Dirichlet function 1Q, and Thomae's function t with t(x)=1/q at a rational x=p/q in lowest terms with q≥1 and t(x)=0 at every irrational x), and write q(x) for the least denominator of a rational x, so that t(x)=1/ι(q(x)) there and t(x)=0 at every irrational x. Then:

  1. 1Q is continuous at no point of 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);
  2. ωt(c)=t(c) for every real c (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals);
  3. t is continuous at every irrational and discontinuous at every rational, so its set of continuity points is exactly R∖Q.

Claim 1 duplicates a companion examples-page argument on purpose. The examples-page proof that the Dirichlet function is nowhere continuous lives on a leaf page of the library, so later A-page items cannot cite it directly. The claim is needed here, and on later pages, as a citable theorem-level statement, so it is proved again rather than quoted. The two statements are the same, and no originality is claimed for the repeated proof. The same duplication pattern is used elsewhere in this page family for examples whose argument also has to be available in A-page form.

Facts & Assumptions

Given: The Dirichlet function 1Q and Thomae's function t, and a real c; N⊆Z⊆Q⊆R are the canonical copies and ι(q)=q⋅1R.

[A1]

1Q(x)=1 for x∈Q and 0 otherwise; t(x)=1/ι(q(x))∈(0,1] for x∈Q and t(x)=0 otherwise, where q(x)=min⁡{q≥1:ι(q)x∈Z} (The Dirichlet function 1Q, and Thomae's function t with t(x)=1/q at a rational x=p/q in lowest terms with q≥1 and t(x)=0 at every irrational x).

[L2]

For every real x there is exactly one integer m with m≤x<m+1, written ⌊x⌋ (Integer part: for every real x there is exactly one integer m with m≤x<m+1); consequently no integer lies strictly between two consecutive integers.

[L3]

For every real η>0 there is a natural N≥1 with 1/ι(N)<η; and ι is positive and strictly increasing on the naturals ≥1, so 1≤q≤N gives ι(q)≤ι(N) and 1/ι(N)≤1/ι(q) (For every ε>0 in a complete ordered field there is a natural n≥1 with 1/n<ε, The canonical natural ι(n)=n⋅1F of a field, Canonical naturals are positive and strictly increasing).

[L4]

A nonempty finite set of reals presented as {a0,…,an} has a minimum (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set).

[L6]

If 0≤u≤M and 0≤v≤M, then −M≤u−v≤M; consequently ∣u−v∣≤M, by the two cases u−v≥0 and u−v<0.

Proof

technique · cases
1.1

Claim 1. Let c be real and let δ>0 be real. The neighbourhood Nδ(c) contains a rational u and an irrational v, and 1Q(u)−1Q(v)=1−0=1; since 1Q(c) is 0 or 1, one of ∣1Q(u)−1Q(c)∣ and ∣1Q(v)−1Q(c)∣ equals 1. So the continuity condition at c fails for ε=1, no δ witnessing it, and 1Q is continuous at no point.

A1L1
1.2

A separation estimate. For a real c and a natural q≥1 put m:=⌊ι(q)c⌋ and define dq(c):=1/ι(q) if ι(q)c=m, and dq(c):=min⁡{ι(q)c−m, m+1−ι(q)c}/ι(q) otherwise. In both cases dq(c)>0.

L2L3construct
1.3

A lower bound. For every real δ>0 the neighbourhood Nδ(c) contains an irrational v, and c∈Nδ(c), so ωt(Nδ(c))≥∣t(c)−t(v)∣=t(c); taking the infimum over δ gives ωt(c)≥t(c).

A1L1L5
2.1

With dq(c) as in step 1.2: for every integer p with p/ι(q)≠c one has ∣c−p/ι(q)∣≥dq(c). If ι(q)c=m then p≠m, so ∣ι(q)c−p∣=∣m−p∣≥1; otherwise m<ι(q)c<m+1, and p≤m gives ι(q)c−p≥ι(q)c−m while p≥m+1 gives p−ι(q)c≥m+1−ι(q)c. Dividing by ι(q)>0 gives the claim.

step 1.2L2L3
2.2

For a real c and a natural N≥1 put δN(c):=min⁡{d1(c),…,dN(c)}, the minimum of a nonempty finite set of positive reals, so δN(c)>0.

step 1.2L4construct
3.1

If x is rational with 0<∣x−c∣<δN(c) then q(x)>N and hence t(x)<1/ι(N). Indeed x=p/ι(q) with q:=q(x) and p:=ι(q)x; if q≤N then p/ι(q)=x≠c, so step 2.1 gives ∣c−x∣≥dq(c)≥δN(c), contrary to the hypothesis. So q(x)>N, and t(x)=1/ι(q(x))<1/ι(N) because ι is strictly increasing.

step 2.1step 2.2A1L3
4.1

An upper bound for t near c. Let ε>0 be real, take N≥1 with 1/ι(N)<ε and put δ:=δN(c). Every x∈Nδ(c) satisfies 0≤t(x)≤M where M:=max⁡{t(c),ε}: for x=c this is t(c)≤M; for x≠c rational it is t(x)<1/ι(N)<ε≤M by step 3.1; and for x irrational it is t(x)=0.

step 3.1A1L3L6
5.1

Hence ωt(Nδ(c))≤M with δ and M as in step 4.1, since ∣t(x)−t(y)∣≤M for all x,y∈Nδ(c), so M is an upper bound of the set whose supremum ωt(Nδ(c)) is; and therefore ωt(c)≤M=max⁡{t(c),ε}.

step 4.1L5L6
6.1

Claim 2 now follows in the two cases of the value t(c), which are exactly the two cases of the position of c. If c is rational then t(c)>0, and applying step 5.1 with the admissible choice ε:=t(c) gives ωt(c)≤max⁡{t(c),t(c)}=t(c); with step 1.3 this gives ωt(c)=t(c).

step 5.1step 1.3A1assume-case rat
6.2

If c is irrational then t(c)=0, and step 5.1 gives ωt(c)≤max⁡{0,ε}=ε for every real ε>0; since also ωt(c)≥0, an extended real that is ≤ε for every positive real ε and ≥0 must be 0, so ωt(c)=0=t(c).

step 5.1step 1.3A1L5assume-case irr
7.1

Every real is rational or irrational and not both, so steps 6.1 and 6.2 establish claim 2 for every real c.

step 6.1step 6.2cases-exhaustive
8.1

Claim 3 follows from claim 2: t is continuous at c exactly when ωt(c)=0, that is exactly when t(c)=0, that is exactly when c is irrational. So the continuity set of t is R∖Q and its discontinuity set is Q.

step 7.1A1L5∎

Remarks

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

Every Gδ subset of R is the set of continuity points of some f:R→R, so the Gδ sets are exactly the continuity sets

Statement

Let G⊆R be a Gδ set (Fσ and Gδ subsets of R). Then there is a function f:R→R whose set of continuity 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) is exactly G.

Together with For f:A→R the set of points of A at which f is discontinuous is the intersection with A of an Fσ subset of R, and the set of points at which f is continuous is the intersection with A of a Gδ subset; for A=R the two sets are Fσ and Gδ outright, which says that the continuity set of every f:R→R is a Gδ set, this identifies the two classes:

{ continuity sets of functions R→R }  =  { Gδ subsets of R }.

The construction. Write G=⋂n∈NVn with each Vn open and put Wn:=V0∩⋯∩Vn, so that the Wn are open and decreasing with ⋂nWn=G. For x∉G let n(x) be the least n with x∉Wn, and set

f(x):=0  for x∈G,f(x):=1ι(n(x)+1)  for x∉G, x∈Q,f(x):=−1ι(n(x)+1)  for x∉G, x∉Q.

The sign carries the whole of the discontinuity: near a point outside G there are points of the opposite rationality, where f has the opposite sign or is 0, and the values cannot come close.

Facts & Assumptions

Given: A Gδ set G=⋂n∈NVn⊆R with each Vn open.

[L2]

Every nonempty subset of N has a least element (The well-ordering principle).

[L4]

For every real η>0 there is a natural m≥1 with 1/ι(m)<η, and ι is positive and strictly increasing on the naturals ≥1, so j<k gives 1/ι(k+1)<1/ι(j+1) (For every ε>0 in a complete ordered field there is a natural n≥1 with 1/n<ε, The canonical natural ι(n)=n⋅1F of a field, Canonical naturals are positive and strictly increasing).

Proof

technique · constructive
1.1

Put Wn:=⋂j≤nVj for n∈N. Each Wn is open, being a finite intersection of open sets; Wn+1⊆Wn; and ⋂nWn=⋂nVn=G, since a point lies in every Wn exactly when it lies in every Vj.

L1construct
2.1

For x∉G the set { n∈N:x∉Wn } is nonempty, so n(x):=min⁡{ n:x∉Wn } is defined; and x∈Wj for every j<n(x), by minimality.

step 1.1L2construct
2.2

f is continuous at every x∈G. Let ε>0 be real and take a natural m≥1 with 1/ι(m)<ε. Since x∈G⊆Wm and Wm is open, there is a real ρ>0 with Nρ(x)⊆Wm.

step 1.1L1L4
3.1

Define f:R→R by f(x):=0 for x∈G, f(x):=1/ι(n(x)+1) for x∉G with x rational, and f(x):=−1/ι(n(x)+1) for x∉G with x irrational. Then f(x)=0 exactly for x∈G, since 1/ι(n+1)>0 for every n∈N; moreover f(x)>0 at a rational outside G and f(x)<0 at an irrational outside G.

step 2.1L4construct
4.1

With m and ρ as in step 2.2, let y∈Nρ(x). If y∈G then f(y)=0. If y∉G then y∈Wm, so n(y)≠m and indeed n(y)>m, because y∈Wm forces y∈Wj for every j≤m; hence ∣f(y)∣=1/ι(n(y)+1)<1/ι(m)<ε, using n(y)+1>m. In both cases ∣f(y)−f(x)∣=∣f(y)∣<ε, since f(x)=0.

step 1.1step 2.1step 3.1step 2.2L4
4.2

f is discontinuous at every x∉G. Put ε:=1/ι(n(x)+1)>0, so that ∣f(x)∣=ε, and let δ>0 be real. If x is rational then f(x)=ε>0; the neighbourhood Nδ(x) contains an irrational y, and f(y)≤0, whether y∈G or not. If x is irrational then f(x)=−ε<0; the neighbourhood Nδ(x) contains a rational y, and f(y)≥0.

step 2.1step 3.1L3
5.1

In either case of step 4.2 the point y satisfies ∣f(y)−f(x)∣≥ε, since f(x) and f(y) have opposite weak signs and ∣f(x)∣=ε. So no δ witnesses the continuity condition at x for this ε, and f is discontinuous at x.

step 4.2
6.1

By steps 4.1 and 5.1 the set of continuity points of the function f constructed in step 3.1 is exactly G, which proves the theorem. Combined with the fact that every continuity set is Gδ, the two classes coincide.

step 3.1step 4.1step 5.1L5discharge-construct∎

Remarks

  • Why the Vn are replaced by the decreasing Wn. The index n(x) is useful only because y∈Wm implies y∈Wj for all j≤m, which is what makes n(y)>m in step 4.1. For an arbitrary sequence (Vn) that implication fails, and n(x) would carry no information about how deep x sits in the intersection. Passing to the finite intersections costs nothing, since they are still open and still intersect to G.

  • Two extreme cases. For G=R the construction gives f=0, continuous everywhere. For G=∅, obtained as the intersection of the sequence constantly ∅, every x lies outside W0=∅, so n(x)=0 and f takes the value 1 at every rational and −1 at every irrational; it is nowhere continuous, as the Dirichlet function is (The Dirichlet function is continuous at no point of R, and Thomae's function is continuous at every irrational and at no rational, so its set of continuity points is exactly the set of irrationals and its oscillation at c equals t(c)).

  • The construction does not guarantee monotonicity, and the theorem does not claim it. The function built above always takes values in [−1,1], so it is bounded; no further behaviour beyond its continuity set is asserted.

CorollaryStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

No function R→R is continuous at every rational and discontinuous at every irrational, because Q is not Gδ

Statement

There is no function f:R→R that is continuous at every rational and discontinuous at every irrational (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 rationals embed densely in the reals).

Equivalently: Q is not the continuity set of any function R→R.

The contrast with Thomae's function is the point. There is a function continuous exactly at the irrationals, namely t (The Dirichlet function is continuous at no point of R, and Thomae's function is continuous at every irrational and at no rational, so its set of continuity points is exactly the set of irrationals and its oscillation at c equals t(c)), and one might expect the two arrangements to be symmetric. They are not, because the classes Fσ and Gδ are exchanged by complementation while Q and the irrationals are, and only one of the two sets is Gδ (Q is Fσ, meager and not Gδ, while the irrationals are Gδ, residual and not Fσ).

Proof

technique · contradiction
1.1

Suppose, for contradiction, that there is f:R→R continuous at every rational and discontinuous at every irrational.

assume-contra
2.1

Then the set of continuity points of f is exactly Q: it contains every rational by hypothesis, and it contains no irrational, again by hypothesis.

step 1.1
3.1

By the Gδ theorem the set of continuity points of f is a Gδ subset of R, so Q is Gδ. This contradicts the fact that Q is not Gδ, so no such f exists.

step 2.1L1L2discharge-contradiction∎

Remarks

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

The intermediate value property (Darboux property) of a function on an interval: the image of every subinterval is order-convex

Definition

Let I⊆R be order-convex (Intervals of R: the nine order-convex forms, nondegeneracy, and length) and let f:I→R. Then f has the intermediate value property, also called the Darboux property, when

f[J] is order-convex for every order-convex J⊆I.

As everywhere in this library, "interval" is read as "order-convex" (A subset of R is connected if and only if it is order-convex, that is, an interval is what licenses the word; Intervals of R: the nine order-convex forms, nondegeneracy, and length records that the classification of the order-convex subsets of R into the nine written forms is not proved here).

The equivalent pointwise form

f has the intermediate value property if and only if

for all a,b∈I with a<b and every real y with f(a)≤y≤f(b) or f(b)≤y≤f(a), there is c∈[a,b] with f(c)=y.

From the displayed condition to the pointwise one. Given a<b in I, the set [a,b] is order-convex and contained in I by order-convexity of I, so f[ [a,b] ] is order-convex; it contains f(a) and f(b), hence every y between them, and such a y is f(c) for some c∈[a,b].

From the pointwise condition to the displayed one. Let J⊆I be order-convex, let u,v∈f[J] and let u≤y≤v. Write u=f(a) and v=f(b) with a,b∈J. If a=b then u=v=y and y∈f[J]. If a<b, the pointwise condition gives c∈[a,b] with f(c)=y, and c∈J because J is order-convex and a,b∈J; so y∈f[J]. If b<a the same argument applies with the roles of a and b exchanged, the pointwise condition being stated symmetrically in the two orders. Hence f[J] is order-convex.

Both forms are used below, and they are used interchangeably.

Every continuous function on an interval has the property

If 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) then f[J] is order-convex for every order-convex J⊆I (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, claim 1). So continuity implies the intermediate value property.

The converse is false, and that is the whole reason the property is given a name of its own: a function may take every intermediate value on every subinterval and be continuous nowhere. The failure is recorded as FALSE: a function with the intermediate value property on an interval is continuous.

A monotone function with the intermediate value property is continuous. This is not a further theorem but a reading of A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous: for a function satisfying f(x)≤f(y) whenever x≤y on an order-convex I, order-convexity of the single image f[I] already forces continuity. So the pathologies live entirely among the non-monotone functions.

DefinitionDefinition: AI-adaptedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Upper and lower semicontinuity of f:A→R at a point of A and on A

Definition

Let A⊆R, let f:A→R and let c∈A, with neighbourhoods as in The ε-neighbourhood and the punctured ε-neighbourhood of a point of R.

  • f is upper semicontinuous at c when for every real ε>0 there is a real δ>0 with f(x)  <  f(c)+εfor every x∈A∩Nδ(c).
  • f is lower semicontinuous at c when for every real ε>0 there is a real δ>0 with f(x)  >  f(c)−εfor every x∈A∩Nδ(c).
  • f is upper semicontinuous on A, respectively lower semicontinuous on A, when it is so at every point of A.

In words: an upper semicontinuous function cannot jump up in the limit, and a lower semicontinuous one cannot jump down. Both conditions are pointwise, both quantify over the same unpunctured neighbourhoods as 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 at x=c each holds automatically, since f(c)<f(c)+ε and f(c)>f(c)−ε.

Continuity is exactly the conjunction

f is continuous at c if and only if it is both upper and lower semicontinuous at c.

If f is continuous at c, a δ witnessing ∣f(x)−f(c)∣<ε on A∩Nδ(c) witnesses both displayed conditions, since ∣f(x)−f(c)∣<ε gives −ε<f(x)−f(c)<ε (Basic properties of the absolute value).

Conversely, given ε>0 take δ1 for the upper condition and δ2 for the lower one and put δ:=min⁡{δ1,δ2}>0. For x∈A∩Nδ(c) both f(x)<f(c)+ε and f(x)>f(c)−ε hold, that is ∣f(x)−f(c)∣<ε (Basic properties of the absolute value). So f is continuous at c.

Consequently f is continuous on A exactly when it is both upper and lower semicontinuous on A.

Negation exchanges the two

f is upper semicontinuous at c if and only if −f is lower semicontinuous at c, since f(x)<f(c)+ε says the same thing as −f(x)>−f(c)−ε (Complete ordered field (least-upper-bound property)). Every statement about one notion below is therefore proved for one of them and transferred to the other by this substitution, never proved twice.

Neither notion implies the other, and neither implies continuity. The indicator of a closed set is upper semicontinuous and the indicator of an open set is lower semicontinuous, and neither is continuous unless the set is clopen; the companion page uses an upper semicontinuous function on [0,1] that attains no minimum.

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

f is upper semicontinuous on A if and only if {x∈A:f(x)<α} is relatively open in A for every real α, lower semicontinuous if and only if {x∈A:f(x)>α} is, and continuous if and only if it is both

Statement

Let A⊆R and let f:A→R. Call S⊆A relatively open in A when S=U∩A for some open U⊆R (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen). Then:

  1. f is upper semicontinuous on A (Upper and lower semicontinuity of f:A→R at a point of A and on A) if and only if { x∈A:f(x)<α } is relatively open in A for every real α;
  2. f is lower semicontinuous on A if and only if { x∈A:f(x)>α } is relatively open in A for every real α;
  3. 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) if and only if both families of sets are relatively open.

The open set is produced canonically, not chosen. For each α the proof exhibits one specific open Uα⊆R with Uα∩A={f<α}, namely the set of reals y admitting a radius ρ with A∩Nρ(y)⊆{f<α}. No choice of a radius per point is made, which matters because the level set may be uncountable.

Facts & Assumptions

Given: A⊆R and a function f:A→R.

[L1]

f is upper semicontinuous 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∩Nδ(c); lower semicontinuity is the same with f(x)>f(c)−ε; and continuity at c is the conjunction of the two (Upper and lower semicontinuity of f:A→R at a point of A and 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).

[L2]

U⊆R is open exactly when every y∈U has a real ρ>0 with Nρ(y)⊆U; and if ∣z−y∣<ρ/2 then Nρ/2(z)⊆Nρ(y) (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]

−f is lower semicontinuous at c exactly when f is upper semicontinuous at c, and {x∈A:−f(x)<α}={x∈A:f(x)>−α} (Upper and lower semicontinuity of f:A→R at a point of A and on A).

Proof

technique · direct
1.1

Fix a real α and put Sα:={ x∈A:f(x)<α } and Uα:={ y∈R:A∩Nρ(y)⊆Sα for some real ρ>0 }.

construct
1.2

Conversely suppose every Sα is relatively open in A, say Sα=U∩A with U open, and let c∈A and ε>0 be real. Put α:=f(c)+ε; then f(c)<α, so c∈Sα=U∩A, and there is a real δ>0 with Nδ(c)⊆U.

L2
2.1

Uα is open: if y∈Uα with witness ρ and z∈Nρ/2(y), then A∩Nρ/2(z)⊆A∩Nρ(y)⊆Sα, so z∈Uα with witness ρ/2; hence Nρ/2(y)⊆Uα.

step 1.1L2
2.2

Uα∩A⊆Sα: if y∈Uα∩A with witness ρ then y∈A∩Nρ(y)⊆Sα.

step 1.1
2.3

Suppose f is upper semicontinuous on A and let c∈Sα. Apply the definition at c with ε:=α−f(c)>0: there is a real δ>0 with f(x)<f(c)+ε=α for every x∈A∩Nδ(c), that is A∩Nδ(c)⊆Sα; so c∈Uα.

step 1.1L1
3.1

Hence Sα⊆Uα∩A, and with step 2.2 this gives Sα=Uα∩A, a relatively open subset of A; since α was arbitrary, one direction of claim 1 holds.

step 2.2step 2.3
4.1

With δ as in step 1.2, every x∈A∩Nδ(c) lies in U∩A=Sα, so f(x)<α=f(c)+ε. As c and ε were arbitrary, f is upper semicontinuous on A, which completes claim 1.

step 3.1step 1.2L1
5.1

Claim 2 follows by applying claim 1 to −f: f is lower semicontinuous on A exactly when −f is upper semicontinuous on A, exactly when {x∈A:−f(x)<β} is relatively open for every real β, and that set is {x∈A:f(x)>−β}; as β ranges over the reals so does −β.

step 4.1L3
6.1

Claim 3 follows: f is continuous on A exactly when it is both upper and lower semicontinuous on A, and by claims 1 and 2 that is exactly the conjunction of the two families of sets being relatively open.

step 4.1step 5.1L1∎

Remarks

  • Why "relatively" open and not open. Sα is a subset of A, so it cannot be open in R unless A is; the correct statement is the one above, exactly as in 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, where the same phrase is fixed inline for the same reason. For A=R the qualifier disappears and the level sets are open outright.

  • The strict inequalities are not interchangeable with the weak ones. Upper semicontinuity says the strict sublevel sets are relatively open, equivalently that the sets {f≥α} are relatively closed. It does not say that the sets {f≤α} are relatively closed; the indicator of a closed set is upper semicontinuous while {f≤0} is the complement of that closed set, which is relatively open and generally not closed.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)verified 2026-08-09 (gpt-5.6-terra-codex-subscription)Open item page →

Semicontinuous extreme value theorem: an upper semicontinuous function on a nonempty compact K⊆R is bounded above and attains a maximum, and a lower semicontinuous one is bounded below and attains a minimum

Statement

Let K⊆R be nonempty and compact (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset).

  1. If f:K→R is upper semicontinuous on K (Upper and lower semicontinuity of f:A→R at a point of A and on A) then f[K] is bounded above (Lower bound, bounded below, bounded set) and f attains a maximum: there is x0∈K with f(x)≤f(x0) for every x∈K (Maximum and minimum of a set).
  2. If f:K→R is lower semicontinuous on K then f[K] is bounded below and f attains a minimum.

The theorem is genuinely one-sided. An upper semicontinuous function on a compact set need not attain its infimum; the companion page gives such a function on [0,1]. Only the maximum is asserted in claim 1, and only the minimum in claim 2.

Taking f continuous, which is upper and lower semicontinuous at once (Upper and lower semicontinuity of f:A→R at a point of A and on A), recovers the classical extreme value theorem on a compact subset of R.

Facts & Assumptions

Given: A nonempty compact K⊆R and an upper semicontinuous f:K→R.

[L2]

The set Uα of [L1] is monotone in α: α≤β gives {f<α}⊆{f<β} and hence Uα⊆Uβ, directly from the displayed description.

[L3]

K compact means: every family of open subsets of R whose union contains K has a finite subfamily whose union contains K (Open cover, subcover, compact subset of R (every open cover has a finite subcover), and sequentially compact subset).

[L4]

For every real x there is a natural n≥1 with x<ι(n), and for every real η>0 a natural n≥1 with 1/ι(n)<η; ι is positive and strictly increasing on the naturals ≥1 (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, The canonical natural ι(n)=n⋅1F of a field, Canonical naturals are positive and strictly increasing).

[L5]

A nonempty set of reals bounded above has a least upper bound, and for every real ε>0 some member of the set exceeds sup⁡−ε (Complete ordered field (least-upper-bound property), Epsilon characterisation of the supremum, Lower bound, bounded below, bounded set).

[L7]

For any h:K→R, h is upper semicontinuous if and only if −h is lower semicontinuous; hence a lower semicontinuous f makes −f upper semicontinuous (Upper and lower semicontinuity of f:A→R at a point of A and on A, section “Negation exchanges the two”).

Proof

technique · direct
1.1

For each real α let Uα be the open set of [L1], so that Uα∩K={x∈K:f(x)<α} and α≤β implies Uα⊆Uβ.

L1L2construct
2.1

The family { Uι(n):n∈N, n≥1 } covers K: every x∈K has f(x)<ι(n) for some natural n≥1, and then x∈Uι(n).

step 1.1L4
3.1

By compactness finitely many members cover K, say Uι(n0),…,Uι(nj) with each ni≥1; let N be the greatest of ι(n0),…,ι(nj), which exists as the maximum of a nonempty finite set of reals. Then each Uι(ni)⊆UN, so K⊆UN and hence K=UN∩K={x∈K:f(x)<N}. So f[K] is bounded above by N.

step 1.1step 2.1L2L3L6
4.1

f[K] is nonempty, since K is, and bounded above, so M:=sup⁡f[K] exists.

step 3.1L5
5.1

For each natural n≥1 put αn:=M−1/ι(n). The family { Uαn:n≥1 } has no finite subfamily covering K. Indeed, let Uαn0,…,Uαnj be finitely many of them; if the list is empty its union is empty and does not contain the nonempty K. Otherwise let n∗ be a natural among n0,…,nj with αn∗ greatest, so that every member of the list is contained in Uαn∗. Since αn∗<M=sup⁡f[K], there is x∈K with f(x)>αn∗, and such an x lies in K but not in Uαn∗∩K={f<αn∗}, hence in no member of the list.

step 1.1step 4.1L2L4L5L6
6.1

By compactness, a family of open sets with no finite subfamily covering K cannot itself cover K. So there is x0∈K with x0∉Uαn for every natural n≥1, that is f(x0)≥αn=M−1/ι(n) for every such n.

step 1.1step 5.1L3
7.1

Hence f(x0)=M. If f(x0)<M then M−f(x0)>0 and there is a natural n≥1 with 1/ι(n)<M−f(x0), that is f(x0)<M−1/ι(n), contradicting step 6.1; and f(x0)≤M because M is an upper bound of f[K].

step 4.1step 6.1L4L5
8.1

So f is bounded above on K and attains the value M=sup⁡f[K] at x0∈K, which is a maximum of f[K]: this is claim 1.

step 3.1step 4.1step 7.1L5
9.1

Claim 2 follows by applying claim 1 to −f, which is upper semicontinuous on K when f is lower semicontinuous; then −f is bounded above and attains a maximum at some x1∈K, so f is bounded below and f(x1)≤f(x) for every x∈K, a minimum.

step 8.1L7∎

Remarks

LemmaStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Baire category inside a closed bounded interval: if [a,b] with a<b is covered by a sequence of closed sets, then one of them contains a nondegenerate closed subinterval of [a,b]; no choice principle is used

Statement

Let a,b∈R with a<b and let (Fn)n∈N be a sequence of closed subsets of R (Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen) with

[a,b]  ⊆  ⋃n∈NFn

(Intervals of R: the nine order-convex forms, nondegeneracy, and length). Then there are n∈N and reals u<v with

[u,v]  ⊆  Fn∩[a,b].

No choice principle is used. The only category input is Baire category in R, by nested intervals with canonically chosen rational endpoints: a countable intersection of dense open sets is dense, so R is not a countable union of nowhere dense sets, whose own proof selects nothing: it fixes one enumeration of the rationals and takes least indices. Nothing further is chosen below, the argument being a direct application of that theorem to the complements of the Fn.

Facts & Assumptions

Given: Reals a<b and a sequence (Fn)n∈N of closed subsets of R with [a,b]⊆⋃nFn.

[L4]

[a,b] is closed: its complement {x:x<a}∪{x:x>b} is open, since x<a gives Na−x(x)⊆{z:z<a} and x>b gives Nx−b(x)⊆{z:z>b} (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, Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L5]

Nε(y)=(y−ε,y+ε), and for a<b the midpoint y:=(a+b)/2 and radius ε:=(b−a)/2>0 give Nε(y)=(a,b)⊆[a,b] (The ε-neighbourhood and the punctured ε-neighbourhood of a point of R, Intervals of R: the nine order-convex forms, nondegeneracy, and length).

Proof

technique · contradiction
1.1

Put Gn:=Fn∩[a,b] for n∈N. Each Gn is closed, being an intersection of two closed sets, and [a,b]=⋃nGn, since [a,b] is contained in the union of the Fn and each Gn is contained in [a,b].

L3L4
1.2

Suppose, for contradiction, that no Gn contains a nondegenerate closed interval, that is, that there are no n and no reals u<v with [u,v]⊆Gn.

assume-contra
2.1

Each Vn:=R∖Gn is open, and it is dense. Openness is the complement of a closed set. For density, let y be real and ε>0 real; if Nε(y)∩Vn were empty then Nε(y)⊆Gn, and then [y−ε/2, y+ε/2] would be a nondegenerate closed interval inside Gn, contrary to step 1.2.

step 1.1step 1.2L2L3L5
3.1

By the Baire category theorem the intersection ⋂nVn is dense in R, so it meets the neighbourhood N(b−a)/2((a+b)/2)=(a,b): there is x∈(a,b) with x∉Gn for every n.

step 2.1L1L2L5
4.1

But x∈(a,b)⊆[a,b]=⋃nGn, so x∈Gn for some n, contradicting step 3.1. The assumption of step 1.2 is therefore false, and some Gn=Fn∩[a,b] contains a nondegenerate closed interval [u,v].

step 1.1step 1.2step 3.1discharge-contradiction∎

Remarks

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Pointwise convergence of a sequence of real functions, and the Baire class one functions as the pointwise limits of sequences of continuous functions

Definition

Let A⊆R. A sequence of functions on A is a function assigning to each n∈N a function fn:A→R; it is written (fn)n∈N. As everywhere in this library N contains 0, so the first term is f0 (Sequences of reals: bounded, eventually, frequently, tails, subsequences).

Pointwise convergence. (fn) converges pointwise on A to f:A→R when, for every x∈A, the sequence of reals (fn(x))n∈N converges to f(x) (Limits and Cauchy sequences of reals); written out, for every x∈A and every real ε>0 there is N∈N with ∣fn(x)−f(x)∣<ε for every n≥N.

The limit function is unique. A sequence of reals has at most one limit (A sequence has at most one limit), so if (fn) converges pointwise to f and to g then f(x)=g(x) for every x∈A, hence f=g. We may therefore speak of the pointwise limit and write f=lim⁡nfn pointwise.

The index N is allowed to depend on x, and that is the whole content of the word pointwise. No uniformity over A is asserted anywhere below.

Baire class one

f:A→R is of Baire class one on A when there is a sequence (fn) of functions A→R, each 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), converging pointwise on A to f.

Every continuous function is of Baire class one, by the constant sequence fn:=f, which converges pointwise to f because a constant sequence of reals converges to its value.

The class is strictly larger than the continuous functions, and it is strictly smaller than the class of all functions. The first is visible already on A=[0,1] (Intervals of R: the nine order-convex forms, nondegeneracy, and length): the indicator of a single point is of Baire class one and is not continuous. The second is Baire's theorem: a Baire class one function on a closed bounded interval [a,b] is continuous at the points of a dense subset of [a,b] that is the trace of a Gδ set, so its set of discontinuities is meager, which shows that a Baire class one function on a closed bounded interval has a dense set of continuity points, and the companion page uses it to exhibit a function that is not of Baire class one.

On the higher classes. The pointwise limits of sequences of Baire class one functions form what is classically called Baire class two, and the construction iterates. No definition of the higher classes is given here and none is used; where the phrase is needed below it is stated as "a pointwise limit of a sequence of Baire class one functions", which is a condition already expressible with the words above.

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

Baire's theorem: a Baire class one function on a closed bounded interval [a,b] is continuous at the points of a dense subset of [a,b] that is the trace of a Gδ set, so its set of discontinuities is meager

Statement

Let a,b∈R with a<b and let f:[a,b]→R be of Baire class one (Pointwise convergence of a sequence of real functions, and the Baire class one functions as the pointwise limits of sequences of continuous functions). Write

D  :=  { x∈[a,b]:f is discontinuous at x },C:=[a,b]∖D

(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. for every real ε>0 the set Dε:={ x∈[a,b]:ωf(x)≥ε } (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals) is a closed subset of R containing no nondegenerate closed interval, hence nowhere dense (Nowhere dense, meager (first category), residual, and second category subsets of R);
  2. D is meager, being the union of the sequence (D1/ι(n+1))n∈N of nowhere dense sets;
  3. C is dense in [a,b]: for every x∈[a,b] and every real ρ>0 the set [a,b]∩Nρ(x) contains a point of C;
  4. C=[a,b]∩V for a Gδ subset V⊆R (Fσ and Gδ subsets of R).

On the phrase "dense Gδ". Claims 3 and 4 together are what the classical statement calls a dense Gδ subset of [a,b]: the continuity set is dense in [a,b] and it is the trace on [a,b] of a Gδ subset of R. It is not claimed that C is Gδ as a subset of R, nor that it is dense in R; neither is true in general, since C⊆[a,b].

Facts & Assumptions

Given: Reals a<b, a function f:[a,b]→R of Baire class one, and a sequence (fk)k∈N of continuous functions on [a,b] converging pointwise to f.

[L2]

ωf(S)=sup⁡{∣f(x)−f(y)∣:x,y∈S}; ωf(x)=inf⁡{ωf([a,b]∩Nδ(x)):δ>0}; ωf is monotone under inclusion and ωf(x)≥0 (The oscillation ωf(S)=sup⁡{ ∣f(x)−f(y)∣:x,y∈S } of f on a set and the oscillation ωf(c)=inf⁡δ>0ωf(A∩Nδ(c)) at a point, both taken in the extended reals).

[L4]

For every real ε>0 there is a closed G⊆R with {x∈[a,b]:ωf(x)≥ε}=[a,b]∩G (For every real ε>0 the set { x∈A:ωf(x)≥ε } is the intersection with A of a closed subset of R; in particular it is closed in R when A=R).

[L5]

If a<b, (Fn) are closed and [a,b]⊆⋃nFn, then some Fn∩[a,b] contains a nondegenerate closed interval (Baire category inside a closed bounded interval: if [a,b] with a<b is covered by a sequence of closed sets, then one of them contains a nondegenerate closed subinterval of [a,b]; no choice principle is used).

[L6]

[a,b] and every [c,d] with c≤d are closed; an intersection of a nonempty family of closed sets is closed; a set is closed exactly when its complement is open (Arbitrary unions and finite intersections of open subsets of R are open, and dually for closed sets, claim 3, Open subset of R (every point has a neighbourhood inside it), closed subset (complement open), and clopen, Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L9]

The set of continuity points of f:A→R is A∩V for a Gδ set V⊆R, and the discontinuity set is {x∈A:ωf(x)>0}=⋃n∈N{x∈A:ωf(x)≥1/ι(n+1)} (For f:A→R the set of points of A at which f is discontinuous is the intersection with A of an Fσ subset of R, and the set of points at which f is continuous is the intersection with A of a Gδ subset; for A=R the two sets are Fσ and Gδ outright, claims 1 and 2, Fσ and Gδ subsets of R).

[L11]

∣u−w∣≤∣u−v∣+∣v−w∣, ∣u∣≥0, and a real that is ≤η for every real η>0 and ≥0 is 0 (Basic properties of the absolute value).

Proof

technique · direct
1.1

Refinement claim. Let [c,d]⊆[a,b] with c<d and let ε>0 be real. For N∈N put EN:={ x∈[c,d]:∣fn(x)−fm(x)∣≤ε/4 for all n,m≥N }.

L1construct
1.2

Claim 1. Fix a real ε>0 and let Dε:={x∈[a,b]:ωf(x)≥ε}. It is closed in R, being [a,b]∩G with G closed and [a,b] closed.

L4L6
1.3

Claim 4. The set of continuity points of f on the domain [a,b] is [a,b]∩V for a Gδ subset V⊆R.

L9
1.4

Claim 3. Let x∈[a,b] and let ρ>0 be real. The set [a,b]∩Nρ(x) contains a nondegenerate closed interval [c,d] with c<d, because a<b: taking c:=max⁡{a, x−ρ/2} and d:=min⁡{b, x+ρ/2} gives [c,d]⊆[a,b]∩Nρ(x) and c<d: if x=a then c=a and d=min⁡{b,a+ρ/2}>a; if x=b then d=b and c=max⁡{a,b−ρ/2}<b; and if a<x<b then c<x<d.

L12
2.1

Each EN is closed: for fixed n,m the set {x∈[c,d]:∣fn(x)−fm(x)∣≤ε/4} is the preimage under the continuous function ∣fn−fm∣ of the closed set {y:y≤ε/4}, hence of the form G∩[c,d] with G closed, hence closed since [c,d] is; and EN is the intersection of that nonempty family of closed sets over the pairs n,m≥N.

step 1.1L6L7
2.2

[c,d]=⋃N∈NEN: for x∈[c,d] the sequence (fk(x)) converges to f(x), so there is N with ∣fk(x)−f(x)∣<ε/8 for all k≥N, and then ∣fn(x)−fm(x)∣≤∣fn(x)−f(x)∣+∣f(x)−fm(x)∣<ε/4 for all n,m≥N.

step 1.1L1L11
3.1

By the interval form of Baire category applied to [c,d] and the sequence (EN), there are N∈N and reals u′<v′ with [u′,v′]⊆EN∩[c,d]=EN.

step 1.1step 2.1step 2.2L5
4.1

For every x∈[u′,v′] one has ∣fN(x)−f(x)∣≤ε/4. Indeed, let η>0 be real; since fm(x)→f(x) there is m≥N with ∣fm(x)−f(x)∣<η, and then ∣fN(x)−f(x)∣≤∣fN(x)−fm(x)∣+∣fm(x)−f(x)∣<ε/4+η; as η>0 was arbitrary this gives ∣fN(x)−f(x)∣≤ε/4.

step 1.1step 3.1L1L11
4.2

Put x0:=(u′+v′)/2, so u′<x0<v′. Since fN is continuous at x0 there is a real δ>0 with ∣fN(x)−fN(x0)∣<ε/4 for every x∈[a,b] with ∣x−x0∣<δ. Put u:=max⁡{u′, x0−δ/2} and v:=min⁡{v′, x0+δ/2}, so that u<x0<v and [u,v]⊆[u′,v′] with ∣x−x0∣<δ for every x∈[u,v].

step 3.1L1L12
5.1

For x,y∈[u,v]: ∣f(x)−f(y)∣≤∣f(x)−fN(x)∣+∣fN(x)−fN(x0)∣+∣fN(x0)−fN(y)∣+∣fN(y)−f(y)∣≤ε/4+ε/4+ε/4+ε/4=ε. Hence ωf([u,v])≤ε, ε being an upper bound of the set whose supremum that is.

step 4.1step 4.2L2L11
6.1

The refinement claim is proved: for every [c,d]⊆[a,b] with c<d and every real ε>0 there are u<v with [u,v]⊆[c,d] and ωf([u,v])≤ε. Moreover every x with u<x<v satisfies ωf(x)≤ε, since [a,b]∩Nρ(x)⊆[u,v] for ρ:=min⁡{x−u, v−x}>0 and ωf is monotone under inclusion.

step 4.2step 5.1L2L12
7.1

Dε contains no nondegenerate closed interval. Were [c,d]⊆Dε with c<d, the refinement claim applied to [c,d] and to the positive real ε/2 would give u<v with [u,v]⊆[c,d] and ωf(x)≤ε/2<ε for every x with u<x<v; such an x lies in [c,d]⊆Dε and so satisfies ωf(x)≥ε, which is impossible.

step 6.1step 1.2
8.1

Hence Dε is nowhere dense: it is closed, so it equals its own closure, and its interior is empty, since an interior point would have a neighbourhood Nρ(x)⊆Dε and then [x−ρ/2, x+ρ/2] would be a nondegenerate closed interval inside Dε.

step 1.2step 7.1L8L12
9.1

Claim 2. D=⋃n∈ND1/ι(n+1), and each D1/ι(n+1) is nowhere dense by step 8.1, so D is a union of a sequence of nowhere dense sets, that is, meager.

step 8.1L8L9L10
10.1

Suppose [c,d]⊆D with c<d as in step 1.4. Then [c,d] is covered by the sequence (D1/ι(n+1)) of closed sets, so by the interval form of Baire category some D1/ι(n+1)∩[c,d] contains a nondegenerate closed interval, contradicting step 7.1. So [c,d]⊈D, and any point of [c,d]∖D is a point of C inside [a,b]∩Nρ(x).

step 7.1step 9.1step 1.4L5L6
11.1

Claims 1, 2, 3 and 4 are therefore proved: claim 1 by steps 1.2, 7.1 and 8.1, claim 2 by step 9.1, claim 3 by steps 1.4 and 10.1, and claim 4 by step 1.3.

step 8.1step 9.1step 1.3step 10.1∎

Remarks

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R

Definition

Let R be the complete ordered field (Complete ordered field (least-upper-bound property), Ordered field, Field). A function f:R→R is additive when it satisfies Cauchy's functional equation

f(x+y)  =  f(x)+f(y)for all x,y∈R.

Equivalently, f is a homomorphism of the additive group of R into itself.

The linear maps are additive. For a fixed real c the function x↦cx satisfies c(x+y)=cx+cy by distributivity, so it is additive. Cauchy's question is whether these are the only additive functions, and the answer is a genuine dichotomy: with any one of a short list of regularity conditions the answer is yes (Six regularity conditions each force an additive f:R→R to be x↦f(1)x: continuity at a single point, monotonicity on a nondegenerate interval, boundedness above on one, boundedness below on one, constancy of sign on one, and a graph that is not dense in R2), and without any of them it is no (FALSE: every additive f:R→R is of the form x↦cx for a single real c).

No continuity, no monotonicity and no measurability is part of the definition. The equation is purely algebraic, and every regularity hypothesis below is stated explicitly where it is used.

A first consequence, recorded here because it is used immediately. An additive f satisfies f(0)=0: putting x=y=0 gives f(0)=f(0)+f(0), and subtracting f(0) gives f(0)=0. The remaining elementary consequences, including f(−x)=−f(x) and Q-homogeneity, are collected in An additive f:R→R satisfies f(0)=0, f(−x)=−f(x) and f(qx)=q f(x) for every rational q and every real x; in particular f(q)=q f(1) at every rational q.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

An additive f:R→R satisfies f(0)=0, f(−x)=−f(x) and f(qx)=q f(x) for every rational q and every real x; in particular f(q)=q f(1) at every rational q

Statement

Let f:R→R be additive (Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R), and identify N⊆Z⊆Q⊆R along the canonical embeddings (The naturals embed in the integers, The integers embed in the rationals, The rationals embed densely in the reals), writing ι(n) for the canonical natural of n in R (The canonical natural ι(n)=n⋅1F of a field). Then, for every real x:

  1. f(0)=0;
  2. f(−x)=−f(x);
  3. f(ι(n) x)=ι(n) f(x) for every n∈N;
  4. f(mx)=m f(x) for every integer m;
  5. f(qx)=q f(x) for every rational q.

In particular, taking x=1 in claim 5, f(q)=q f(1) at every rational q: an additive function is determined on Q by its value at 1.

What this does not say. Claim 5 is Q-homogeneity, not R-homogeneity: nothing here gives f(λx)=λf(x) for irrational λ, and that is exactly the gap that FALSE: every additive f:R→R is of the form x↦cx for a single real c shows cannot be closed without a regularity hypothesis.

Facts & Assumptions

Given: An additive f:R→R, so f(x+y)=f(x)+f(y) for all reals x,y.

[L3]

Every integer is ι(n) or −ι(n) for a natural n, and every rational is m/ι(n) with m an integer and n a natural ≥1; the embeddings preserve sums and products, and ι(n)≠0 for n≥1 (The naturals embed in the integers, The integers embed in the rationals, The rationals embed densely in the reals, The integers as equivalence classes of pairs of naturals, Canonical naturals are positive and strictly increasing).

[L4]

R is a field, so cancellation, distributivity and inverses of nonzero elements are available (Complete ordered field (least-upper-bound property)).

Proof

technique · induction
1.1

Claim 1: taking x=y=0 in the functional equation gives f(0)=f(0)+f(0), and adding −f(0) to both sides gives f(0)=0.

A1L4
1.2

Claim 3, inductive hypothesis: suppose f(ι(n)x)=ι(n)f(x) for a given n∈N and every real x.

ih
2.1

Claim 2: taking y=−x gives 0=f(0)=f(x)+f(−x), so f(−x)=−f(x).

step 1.1A1L4
2.2

Claim 3, base case n=0: ι(0)=0, so f(ι(0)x)=f(0)=0=ι(0)f(x).

step 1.1L2base
2.3

Claim 3, inductive step: ι(n+1)x=ι(n)x+x, so f(ι(n+1)x)=f(ι(n)x)+f(x)=ι(n)f(x)+f(x)=(ι(n)+1)f(x)=ι(n+1)f(x).

step 1.2A1L2L4
3.1

Claim 3 holds for every n∈N and every real x, by induction on n from steps 2.2 and 2.3.

step 2.2step 2.3L1
4.1

Claim 4: an integer m is ι(n) or −ι(n) for some natural n. In the first case claim 3 applies directly. In the second, f(mx)=f(−(ι(n)x))=−f(ι(n)x)=−ι(n)f(x)=mf(x).

step 2.1step 3.1L3
5.1

Claim 5: let q be rational and write q=m/ι(n) with m an integer and n a natural ≥1, so ι(n)≠0. Applying claim 4 with the integer ι(n) to the real qx gives ι(n)f(qx)=f(ι(n)qx)=f(mx)=mf(x), and dividing by ι(n) gives f(qx)=(m/ι(n))f(x)=qf(x).

step 4.1L3L4
6.1

Taking x=1 in claim 5 gives f(q)=qf(1) for every rational q, and all five claims are proved.

step 1.1step 2.1step 3.1step 4.1step 5.1discharge-induction∎

Remarks

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

If an additive f:R→R is bounded above on some nondegenerate interval, then f(x)=f(1) x for every real x

Statement

Let f:R→R be additive (Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R) and suppose there are reals p<r and a real M with f(z)≤M for every z∈[p,r]; that is, f is bounded above on a nondegenerate interval (Intervals of R: the nine order-convex forms, nondegeneracy, and length, Lower bound, bounded below, bounded set). Then

f(x)  =  f(1) xfor every real x.

A nondegenerate interval is all that is needed, and its position is irrelevant. Any order-convex set with two distinct points contains a closed [p,r] with p<r, and the hypothesis is used only through that closed interval; the argument then translates the interval along Q to cover the whole line.

Facts & Assumptions

Given: An additive f:R→R, reals p<r, and a real M with f(z)≤M for every z∈[p,r].

[A2]
[L1]

An additive f satisfies f(0)=0, f(−x)=−f(x), f(qx)=qf(x) for every rational q and every real x, and f(ι(n)x)=ι(n)f(x) for every n∈N (An additive f:R→R satisfies f(0)=0, f(−x)=−f(x) and f(qx)=q f(x) for every rational q and every real x; in particular f(q)=q f(1) at every rational q).

[L2]

Strictly between any two distinct reals there lies a rational (The rationals embed densely in the reals).

[L4]

R is an ordered field: sums and products of positives are positive, and u>0 with v≥u gives v>0 (Complete ordered field (least-upper-bound property), Basic properties of the absolute value).

Proof

technique · direct
1.1

Put c:=f(1) and define g:R→R by g(x):=f(x)−c x. Then g is additive, since both f and x↦cx are, and g(q)=f(q)−cq=qf(1)−cq=0 for every rational q.

A1L1construct
2.1

g is bounded above on [p,r]: for z∈[p,r] one has g(z)=f(z)−cz≤M+∣c∣ K, where K:=max⁡{∣p∣,∣r∣}, because ∣cz∣≤∣c∣ ∣z∣≤∣c∣ K and hence −cz≤∣c∣ K. Write M′:=M+∣c∣ K for this bound.

step 1.1A2L4
2.2

g(x+q)=g(x) for every real x and every rational q: additivity gives g(x+q)=g(x)+g(q) and g(q)=0.

step 1.1
2.3

g is identically 0. Suppose g(x0)≠0 for some real x0. Replacing x0 by −x0 if necessary, which changes the sign of g(x0) since g(−x)=−g(x), we may take g(x0)>0.

step 1.1L1
3.1

g is bounded above by M′ on the whole of R. Let x be real. The two reals x−r and x−p satisfy x−r<x−p, so there is a rational q with x−r<q<x−p; then p<x−q<r, so x−q∈[p,r] and g(x)=g((x−q)+q)=g(x−q)≤M′.

step 2.1step 2.2L2
4.1

With x0 as in step 2.3, take a natural n≥1 with M′/g(x0)<ι(n); then ι(n) g(x0)>M′. But g(ι(n)x0)=ι(n) g(x0)>M′, contradicting step 3.1. So no such x0 exists and g vanishes identically.

step 1.1step 3.1step 2.3L1L3L4
5.1

Therefore f(x)=c x=f(1) x for every real x.

step 1.1step 4.1∎

Remarks

TheoremStatement: AI-adaptedProof: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Six regularity conditions each force an additive f:R→R to be x↦f(1)x: continuity at a single point, monotonicity on a nondegenerate interval, boundedness above on one, boundedness below on one, constancy of sign on one, and a graph that is not dense in R2

Statement

Let f:R→R be additive (Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R) and put c:=f(1). Write R2 for the set of functions 2→R with the metric d∞((a,b),(a′,b′))=max⁡{∣a−a′∣, ∣b−b′∣} (Rn as the set of functions n→R, and d1, d2, d∞ are metrics on it, Metric space: d(x,y)=0 iff x=y, symmetry, and the triangle inequality; pseudometric and ultrametric), and let

Γ  :=  { (x,f(x))  :  x∈R }  ⊆  R2

be the graph of f. If any one of the following six conditions holds, then f(x)=c x for every real x.

  1. f is continuous at some single point of 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).
  2. f is monotone on some nondegenerate interval (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences, Intervals of R: the nine order-convex forms, nondegeneracy, and length).
  3. f is bounded above on some nondegenerate interval (Lower bound, bounded below, bounded set).
  4. f is bounded below on some nondegenerate interval.
  5. f has constant sign on some nondegenerate interval I: either f(z)≥0 for every z∈I, or f(z)≤0 for every z∈I.
  6. Γ is not dense in R2 (Interior, closure, boundary, limit point, isolated point and dense subset of a metric space).

Conditions 3, 4 and 5 are not independent, and the proof does not pretend they are. Condition 5 is the special case of 3 or of 4 with the bound 0, and condition 4 is condition 3 applied to −f; they are listed separately only because each is the form in which the hypothesis usually arises. Condition 1 and condition 2 are each reduced to condition 3 in one line. Condition 6 is the only one that is not, and it is proved in the contrapositive: if f is not of the form x↦cx, then Γ is dense.

Two classical clauses are absent. Boundedness on a set of positive measure and Lebesgue measurability also force linearity, and neither is stated here: both require a measure, and this library develops none as it stands. Each is an independent sufficient condition, so restoring them would change nothing else on this page.

Facts & Assumptions

Given: An additive f:R→R with c:=f(1), and its graph Γ={(x,f(x)):x∈R}.

[L1]
[L2]

If an additive g is bounded above on some [p,r] with p<r, then g(x)=g(1)x for every real x (If an additive f:R→R is bounded above on some nondegenerate interval, then f(x)=f(1) x for every real x).

[L3]

A nondegenerate interval contains a closed [p,r] with p<r, by order-convexity (Intervals of R: the nine order-convex forms, nondegeneracy, and length).

[L4]

f continuous at c0 means: for every real ε>0 there is a real δ>0 with ∣f(x)−f(c0)∣<ε whenever ∣x−c0∣<δ; and ∣u∣<ε gives u<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, The ε-neighbourhood and the punctured ε-neighbourhood of a point of R, Basic properties of the absolute value).

[L5]

f nondecreasing on I means f(x)≤f(y) for x≤y in I, and nonincreasing means f(x)≥f(y); monotone means one of the two (Nondecreasing, increasing (strictly increasing), nonincreasing, decreasing, monotone and strictly monotone real functions on a subset of R, with the dictionary to monotone sequences).

[L6]

d∞ is a metric on R2 and its open ball of centre (a,b) and radius ε is {(u,v):∣u−a∣<ε and ∣v−b∣<ε}; a subset S of a metric space is dense exactly when every open ball meets S (Rn as the set of functions n→R, and d1, d2, d∞ are metrics on it, Open ball, closed ball and sphere in a metric space, Interior, closure, boundary, limit point, isolated point and dense subset of a metric space, The closure of a nonempty A is {x:d(x,A)=0}, equals A together with its limit points, and is the smallest closed superset).

Proof

technique · cases
1.1

Assume at least one of the six conditions holds. The six steps below treat the six conditions in turn and are exhaustive for that assumption; in each the conclusion reached is f(x)=cx for every real x.

construct
2.1

Condition 3. If f is bounded above on a nondegenerate interval, that interval contains a closed [p,r] with p<r on which f is bounded above, and the boundedness lemma gives f(x)=f(1)x=cx for every real x.

step 1.1L2L3assume-case above
2.2

Condition 6, in the contrapositive: if f is not x↦cx then Γ is dense in R2. Suppose f(x2)≠c x2 for some real x2. Then x2≠0, since f(0)=0. Put x1:=1, v1:=(x1,f(x1))=(1,c) and v2:=(x2,f(x2)), and put Δ:=x1f(x2)−x2f(x1)=f(x2)−c x2, which is nonzero by assumption.

step 1.1L1assume-case graph
3.1

Condition 4. If f is bounded below on a nondegenerate interval I, say f(z)≥m for z∈I, then −f is additive and satisfies −f(z)≤−m on I, so −f is bounded above on I; by step 2.1 applied to −f we get −f(x)=(−f)(1) x=−cx, hence f(x)=cx.

step 2.1A1assume-case below
3.2

Condition 2. Let f be monotone on a nondegenerate interval, which contains [p,r] with p<r. If f is nondecreasing there then f(z)≤f(r) for every z∈[p,r], and if f is nonincreasing there then f(z)≤f(p); either way f is bounded above on [p,r] and step 2.1 applies.

step 2.1L3L5assume-case mono
3.3

Condition 1. Let f be continuous at a point c0. Taking ε:=1 gives a real δ>0 with ∣f(x)−f(c0)∣<1, hence f(x)<f(c0)+1, for every x with ∣x−c0∣<δ. The set of such x is the nondegenerate interval (c0−δ, c0+δ), so f is bounded above on a nondegenerate interval and step 2.1 applies.

step 2.1L3L4assume-case cont
3.4

Let (a,b)∈R2 and let ε>0 be real. Put α:=(a f(x2)−b x2)/Δ and β:=(b x1−a f(x1))/Δ. Then αx1+βx2=a and αf(x1)+βf(x2)=b, as multiplying out and cancelling Δ shows in each case.

step 2.2L7
4.1

Condition 5. If f(z)≥0 for every z in a nondegenerate interval I then f is bounded below on I by 0 and step 3.1 applies; if f(z)≤0 for every z∈I then f is bounded above on I by 0 and step 2.1 applies. So sign-constancy is a special case of the two preceding conditions and needs no separate argument.

step 2.1step 3.1assume-case sign
4.2

Choose rationals q1,q2 with ∣q1−α∣<η and ∣q2−β∣<η, where η>0 is a real chosen with η (∣x1∣+∣x2∣)<ε and η (∣f(x1)∣+∣f(x2)∣)<ε; such rationals exist because a rational lies strictly between any two distinct reals, and such an η exists because for a real K≥0 the inequality ηK<ε holds for all small enough η>0.

step 3.4L7
5.1

Put x:=q1x1+q2x2. Then f(x)=q1f(x1)+q2f(x2) by additivity and rational homogeneity, so (x,f(x))∈Γ. Moreover ∣x−a∣=∣(q1−α)x1+(q2−β)x2∣≤η(∣x1∣+∣x2∣)<ε and likewise ∣f(x)−b∣≤η(∣f(x1)∣+∣f(x2)∣)<ε.

step 3.4step 4.2A1L1L7
6.1

So every open ball of R2 meets Γ, that is, Γ is dense in R2. Reading this contrapositively: if Γ is not dense in R2 then f(x)=cx for every real x, which is condition 6.

step 2.2step 5.1L6
7.1

Each of the six conditions has now been shown to force f(x)=cx for every real x: condition 1 at step 3.3, condition 2 at step 3.2, condition 3 at step 2.1, condition 4 at step 3.1, condition 5 at step 4.1 and condition 6 at step 6.1.

step 2.1step 3.1step 4.1step 3.2step 3.3step 6.1cases-exhaustive∎

Remarks

  • Every clause reduces to one lemma. The engine is If an additive f:R→R is bounded above on some nondegenerate interval, then f(x)=f(1) x for every real x; five of the six conditions are shown to imply its hypothesis, and the sixth is proved separately because a non-dense graph gives no bound on f anywhere. The economy is deliberate: proving each clause from scratch would repeat the same translation-and-scaling argument five times.

  • The list is not a list of equivalent conditions. Each of the six implies linearity, and linearity implies all six, so over the additive functions they are indeed equivalent; but the theorem as stated is six implications in one direction, and that is what the proof establishes.

  • None of the six is dispensable in the sense that additivity alone suffices. There is an additive f satisfying none of them (FALSE: every additive f:R→R is of the form x↦cx for a single real c), and by the theorem it is unbounded above and below on every nondegenerate interval, monotone on none, continuous at no point, of constant sign on no nondegenerate interval, and has dense graph. The construction costs the Axiom of Choice, and the companion page records what it looks like.

LemmaStatement: AI-adaptedProof: AI-generatedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

Assuming the Axiom of Choice, R has a Hamel basis over Q: there is B⊆R such that every real is a finite Q-linear combination of elements of B in exactly one way, and each basis vector carries a well-defined Q-linear coefficient map

Statement

Assume the Axiom of Choice (The Axiom of Choice). The hypothesis is genuinely used: it enters through Every vector space has a basis, whose own Statement begins "Assume the Axiom of Choice", and which rests on Zorn's lemma.

Write Q for the canonical copy {q^:q∈Q} of the rationals inside R (The rationals embed densely in the reals). Then Q is a subfield of R (Subfield: a subring of a field closed under inverses of its nonzero elements, and therefore a field with the restricted operations) and R is a vector space over Q by restriction of scalars (A field is a vector space over itself, and over any subfield K⊆F every F-vector space is a K-vector space by restricting the scalars, Vector space over a field); all spans, linear independence and bases below are taken in that structure. Then:

  1. Existence. R has a basis B over Q (Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis), called a Hamel basis.
  2. Representation. Every real x is x=∑i<nλibi for some n∈N, some injective list b:n→B (Injection, surjection, bijection) and some λ:n→Q (Linear combination of a finite list, and the span span⁡(S) as the smallest linear subspace containing S).
  3. Uniqueness along a list. For a fixed n and a fixed injective b:n→B, if λ,μ:n→Q satisfy ∑i<nλibi=∑i<nμibi, then λi=μi for every i<n.
  4. The coefficient map of a basis vector. Fix b⋆∈B and put Wb⋆:=span⁡(B∖{b⋆}). Every real x is x=λ b⋆+w with λ∈Q and w∈Wb⋆ in exactly one way. Writing Λb⋆(x):=λ for that unique scalar, the map Λb⋆:R→Q satisfies Λb⋆(x+y)=Λb⋆(x)+Λb⋆(y),Λb⋆(qx)=q Λb⋆(x)  (q∈Q),Λb⋆(b⋆)=1, its range is the whole of Q, and { x∈R:Λb⋆(x)=0 }=Wb⋆.
  5. The complement is not trivial. Wb⋆≠{0} for every b⋆∈B.

Claim 2 together with claim 4 is the precise content of the phrase "in exactly one way" in the title: a real is a finite Q-combination of basis vectors, and the coefficient attached to each single basis vector is determined by the real alone.

Facts & Assumptions

Given: The field R, the canonical copy Q⊆R of the rationals, and the Axiom of Choice.

[A1]

The Axiom of Choice, used only through [L4] (The Axiom of Choice, Zorn's lemma).

[L1]

The map q↦q^ is an embedding of ordered fields of Q into R (The rationals embed densely in the reals); a subfield is a subset containing 1, closed under a−b and ab, and containing x−1 for each nonzero x in it (Subfield: a subring of a field closed under inverses of its nonzero elements, and therefore a field with the restricted operations, Field, Complete ordered field (least-upper-bound property)).

[L2]

A field is a vector space over itself, and an F-vector space is a K-vector space for every subfield K⊆F by restricting the scalars (A field is a vector space over itself, and over any subfield K⊆F every F-vector space is a K-vector space by restricting the scalars, Vector space over a field).

[L5]

For S⊆V: S is linearly dependent if and only if some s∈S lies in span⁡(S∖{s}); and span⁡(S) is already the set of linear combinations of injective finite lists into S (A subset S⊆V is linearly dependent if and only if some s∈S lies in span⁡(S∖{s}); and span⁡(S) is already the set of linear combinations of INJECTIVE finite lists into S, claims 1 and 2, span⁡(S) is exactly the set of linear combinations of finite lists of elements of S, and span⁡(∅)={0V}).

[L6]

A finite list v:n→V is an ordered basis of V if and only if every x∈V is ∑i<nλivi for exactly one λ:n→F; an ordered basis is an injective list whose image is a basis; and for a linear subspace U⊆V and A⊆U the readings of "A is linearly independent" and "A is a basis" computed in U and in V agree (A finite list v:n→V is an ordered basis if and only if every x∈V equals ∑i<nλivi for exactly one λ:n→F; those scalars are the coordinates of x in that ordered basis, Basis of a vector space: a linearly independent spanning subset; and ordered basis: an injective finite list whose image is a basis, The natural numbers N (von Neumann)).

[L8]

Q≈N and R is uncountable; a nonempty at most countable set is the image of a surjection from N, and the image of a surjection from N is at most countable (Q is countably infinite, R is uncountable (Cantor's nested intervals, 1874), A nonempty set is at most countable iff it is a surjective image of N, Finite, countably infinite, countable, uncountable).

Proof

technique · direct
1.1

Q={q^:q∈Q} is a subfield of R: it contains 1^=1; it is closed under differences and products, since p^−q^=p−q^ and p^ q^=pq^; and if q^≠0 then q≠0 and q^−1=q−1^ lies in it.

L1
2.1

R is a vector space over itself, so restricting the scalars to the subfield Q makes R a vector space over Q, with the field addition as vector addition and the field multiplication restricted to Q×R as scalar multiplication.

step 1.1L2
3.1

Claim 1: assuming the Axiom of Choice, that vector space has a basis B, a linearly independent subset of R with span⁡(B)=R.

step 2.1A1L4
4.1

Claim 2: since span⁡(B)=R and the span of a set is already the set of linear combinations of injective finite lists into it, every real x is ∑i<nλibi with b:n→B injective and λ:n→Q.

step 3.1L5
4.2

Claim 3: let b:n→B be injective and put U:=span⁡(b[n]), a linear subspace of R. The list b is linearly independent, since B is a linearly independent subset and b is an injective finite list into B; its image b[n] spans U by construction, so b[n] is a basis of U and b is an ordered basis of U, independence and spanning being the same conditions read in U as in R.

step 3.1L3L6
4.3

Fix b⋆∈B and put U0:=span⁡{b⋆}={ λb⋆:λ∈Q } and U1:=Wb⋆=span⁡(B∖{b⋆}), both linear subspaces of R.

step 3.1L3construct
5.1

With b and U as in step 4.2, the coordinate theorem applied to the vector space U says that every x∈U is ∑i<nλibi for exactly one λ:n→Q; in particular ∑i<nλibi=∑i<nμibi forces λ=μ, which is claim 3.

step 4.2L6
5.2

U0+U1=R. Indeed U0+U1=span⁡(U0∪U1); the set B is contained in U0∪U1, since b⋆∈U0 and B∖{b⋆}⊆U1 by extensiveness of the span, so R=span⁡(B)⊆span⁡(U0∪U1) by monotonicity; and U0∪U1⊆span⁡(B), again by monotonicity, so span⁡(U0∪U1)⊆span⁡(span⁡(B))=span⁡(B)=R by idempotence.

step 3.1step 4.3L3L7
5.3

b⋆≠0 and b⋆∉U1. If b⋆ lay in span⁡(B∖{b⋆}) then B would be linearly dependent, contrary to step 3.1; and 0∈B would likewise make B dependent, since 0∈span⁡(B∖{0}), every span containing the zero vector.

step 3.1step 4.3L5
6.1

U0∩U1={0}. Let z∈U0∩U1 and write z=λb⋆ with λ∈Q. If λ≠0 then b⋆=λ−1z∈U1, because U1 is a linear subspace and λ−1∈Q, contradicting step 5.3; so λ=0 and z=0.

step 4.3step 5.3L3
7.1

Hence R=U0⊕U1: condition (D1) is step 5.2, and condition (D2) is step 6.1, since for the two-member family the sum of the other summands is U1 in the one case and U0 in the other. By the direct-sum criterion every real x is u0+u1 with u0∈U0 and u1∈U1 in exactly one way.

step 5.2step 6.1L7
8.1

Writing u0=λb⋆, the scalar λ∈Q is determined by u0, since b⋆≠0; so Λb⋆(x):=λ is a well-defined map R→Q, and x=Λb⋆(x) b⋆+w with w∈Wb⋆ in exactly one way.

step 5.3step 7.1L3
9.1

Λb⋆ is additive and Q-homogeneous: if x=λb⋆+w and y=μb⋆+w′ with w,w′∈Wb⋆, then x+y=(λ+μ)b⋆+(w+w′) with w+w′∈Wb⋆, and qx=(qλ)b⋆+qw with qw∈Wb⋆ for q∈Q, both because Wb⋆ is a linear subspace; uniqueness in step 8.1 then identifies the coefficients.

step 8.1L3
10.1

Λb⋆(b⋆)=1, from the representation b⋆=1⋅b⋆+0; the range of Λb⋆ is all of Q, since Λb⋆(qb⋆)=q for every q∈Q; and Λb⋆(x)=0 holds exactly when x=0⋅b⋆+w=w∈Wb⋆. Claim 4 is proved.

step 8.1step 9.1
11.1

Claim 5: if Wb⋆={0} then step 8.1 gives R={λb⋆:λ∈Q}. That set is the image of Q under λ↦λb⋆, and Q is the image of a surjection from N, so composing gives a surjection from N onto R and R would be at most countable, contradicting its uncountability. So Wb⋆≠{0}.

step 8.1L8∎

Remarks

  • How this differs from R as a vector space over Q has a basis, and every such basis is infinite; the existence proof exhibits none, exactly. That item, homed on the examples page of Linear independence, bases and dimension, proves three things: that R is a vector space over the canonical copy of Q, that it has a basis there, and that every such basis is infinite, together with the observation that the existence proof exhibits none. The present lemma proves the first two and does not prove the third: nothing above says that a Hamel basis is infinite. What it adds instead is claims 2 to 5 — the representation by injective lists, uniqueness of the coefficients along a list, the coefficient map Λb⋆ of a single basis vector with its kernel, and the fact that Wb⋆≠{0} — none of which appears there. So neither statement contains the other, and they are not the same statement.

The duplication of the two shared clauses is deliberate. An examples page is a leaf of this library and nothing outside it may depend on an item homed there, so a citable Hamel basis had to be built on a page that is not a leaf. The proofs of those clauses are the same proof, and no originality is claimed for them.

5 · Examples, counterexamples and false statements

False statementConstruction: Literature-sourcedVerification: AI-adaptedprecheck passjudge pass (z-ai/glm-5.2)audited 2026-07-28Open item page →

FALSE: a function with the intermediate value property on an interval is continuous

Statement

Facts & Assumptions

[L1]

For every real u there is exactly one integer m with m≤u<m+1, written ⌊u⌋ (Integer part: for every real x there is exactly one integer m with m≤x<m+1); in particular no integer lies strictly between m and m+1.

[L2]

min⁡{a,b} and max⁡{a,b} exist for reals a,b, and a nonempty finite set of reals has a minimum and a maximum (Maximum and minimum of a set, Every nonempty finite set of reals has a maximum and a minimum).

[L3]

Sums, scalar multiples, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants and the identity; composites of continuous functions are continuous (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, A composite of continuous functions is continuous, with no side hypothesis of the kind the composition of limits needs).

[L4]

Intermediate value theorem: a continuous function on [a,b] takes every value between its values at the endpoints (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)).

[L6]

∣u∣≥0, ∣u∣=0 only for u=0, and ∣u−w∣≤∣u−v∣+∣v−w∣ (Basic properties of the absolute value).

[L7]

f has the intermediate value property on an order-convex I exactly when for all a<b in I and every y between f(a) and f(b) in either order there is c∈[a,b] with f(c)=y (The intermediate value property (Darboux property) of a function on an interval: the image of every subinterval is order-convex).

Refutation

technique · direct
1.1

Define ψ:R→R by ψ(u):=min⁡{ u−⌊u⌋, ⌊u⌋+1−u }, the distance from u to the nearest integer, and define g:[−1,1]→R by g(x):=ψ(1/x) for x≠0 and g(0):=0.

L1L2construct
2.1

0≤ψ(u)≤1/2 for every real u: writing θ:=u−⌊u⌋∈[0,1), the two entries are θ≥0 and 1−θ>0, and their minimum is at most their average 1/2. Consequently 0≤g(x)≤1/2 for every x∈[−1,1].

step 1.1L1L2
2.2

ψ(u)=min⁡{ ∣u−m∣:m∈Z } in the sense that ∣u−m∣≥ψ(u) for every integer m, with equality for m=⌊u⌋ or m=⌊u⌋+1. Indeed, with n:=⌊u⌋: for m≤n one has ∣u−m∣=u−m≥u−n, and for m≥n+1 one has ∣u−m∣=m−u≥n+1−u.

step 1.1L1
2.3

For every real η>0 and every y∈[0,1/2] there is x with 0<x<η and g(x)=y: take a natural k≥1 with 1/ι(k)<η and put x:=1/(ι(k)+y). Then 0<x≤1/ι(k)<η and 1/x=ι(k)+y with 0≤y≤1/2<1, so ⌊1/x⌋=ι(k) and ψ(1/x)=min⁡{y,1−y}=y.

step 1.1L1L5
3.1

ψ is continuous on R, because ∣ψ(u)−ψ(v)∣≤∣u−v∣ for all reals u,v: choose an integer m with ∣u−m∣=ψ(u), which exists by step 2.2; then ψ(v)≤∣v−m∣≤∣v−u∣+∣u−m∣=∣u−v∣+ψ(u), and exchanging u and v gives the other inequality. So δ:=ε witnesses continuity at every point.

step 2.2L6
3.2

For every real η>0 and every y∈[0,1/2] there is x with −η<x<0 and g(x)=y: with k as in step 2.3 put x:=−1/(ι(k)+y), so −η<x<0 and 1/x=−ι(k)−y. If y=0 then 1/x=−ι(k) is an integer and ψ(1/x)=0=y; if 0<y≤1/2 then ⌊1/x⌋=−ι(k)−1 and 1/x−⌊1/x⌋=1−y, so ψ(1/x)=min⁡{1−y,y}=y.

step 1.1step 2.3L1L5
3.3

g is discontinuous at 0: g(0)=0, and by step 2.3 every real δ>0 admits x with 0<x<δ and g(x)=1/2, so ∣g(x)−g(0)∣=1/2. Hence no δ witnesses the continuity condition at 0 for ε:=1/2.

step 1.1step 2.3L6
4.1

g is continuous at every x∈[−1,1] with x≠0: on the set {x∈[−1,1]:x≠0} the map x↦1/x is continuous, and g is its composite with ψ; continuity at a point of that set is continuity of g there, since the set contains a whole neighbourhood of x inside [−1,1] when x≠0.

step 1.1step 3.1L3
4.2

If 0∈[a,b] then, since a<b, either b>0 or a<0. In the first case step 2.3 with η:=b gives c with 0<c<b and g(c)=y, and c∈[a,b]; in the second case step 3.2 with η:=−a gives c with a<c<0 and g(c)=y. Either way y∈g[ [a,b] ].

step 2.1step 2.3step 3.2L7
5.1

g has the intermediate value property on [−1,1]. Let a<b in [−1,1] and let y lie between g(a) and g(b) in either order; in particular y∈[0,1/2] by step 2.1. If 0∉[a,b] then g restricted to [a,b] is continuous by step 4.1, and the intermediate value theorem supplies c∈[a,b] with g(c)=y.

step 2.1step 4.1L4L7
6.1

So g is a function on the interval [−1,1] with the intermediate value property that is not continuous on [−1,1], and the claim in the Statement is false.

step 3.3step 5.1step 4.2L7discharge-construct∎

Remarks

  • What survives the refutation. The implication continuous ⇒ intermediate value property is true and is 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. So is the partial converse for monotone functions: a function satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous (A function on an interval satisfying f(x)≤f(y) whenever x≤y, whose image is order-convex, is continuous). The witness above is therefore necessarily non-monotone, and it is: it rises and falls infinitely often in every neighbourhood of 0.

  • The witness fails continuity at exactly one point. That is all a refutation needs, and it is all that is claimed: nothing above says that the failure cannot be worse. Functions with the intermediate value property that are continuous at no point at all do exist, the standard one being Conway's base-13 function; it is not constructed at this point in the reading order, and no statement here depends on it.

  • Nothing above defines the derivative, and Darboux's theorem is not used. The classical source of non-continuous functions with the intermediate value property is the class of derivatives, which have the property by Darboux's theorem; no notion of derivative is available at this point in the reading order, and the witness here is built by hand instead.

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

FALSE: every additive f:R→R is of the form x↦cx for a single real c

Statement

FALSE. Every additive f:R→R (Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R) is of the form x↦c x for a single real c.

What is true is the Q-linear part of it, f(qx)=qf(x) for rational q (An additive f:R→R satisfies f(0)=0, f(−x)=−f(x) and f(qx)=q f(x) for every rational q and every real x; in particular f(q)=q f(1) at every rational q), and the conditional statements of Six regularity conditions each force an additive f:R→R to be x↦f(1)x: continuity at a single point, monotonicity on a nondegenerate interval, boundedness above on one, boundedness below on one, constancy of sign on one, and a graph that is not dense in R2, each of which adds a regularity hypothesis. The claim above asserts the conclusion with no hypothesis at all, and it is false.

The refutation assumes the Axiom of Choice (The Axiom of Choice), which it uses through Assuming the Axiom of Choice, R has a Hamel basis over Q: there is B⊆R such that every real is a finite Q-linear combination of elements of B in exactly one way, and each basis vector carries a well-defined Q-linear coefficient map and hence through Zorn's lemma. The hypothesis is carried explicitly in the Facts below and in every step that needs it. It is an axiom already adopted in this library, so the refutation is a refutation and not a conditional one; what it does not settle is whether a counterexample exists without choice, and nothing here bears on that question.

Facts & Assumptions

Given: The Axiom of Choice, and Q denoting the canonical copy of the rationals inside R (The rationals embed densely in the reals).

[A1]

The Axiom of Choice (The Axiom of Choice, Zorn's lemma).

[L1]

Assume the Axiom of Choice. Then there is B⊆R, a basis of R as a vector space over Q by restriction of scalars, and for each b⋆∈B a map Λb⋆:R→Q with Λb⋆(x+y)=Λb⋆(x)+Λb⋆(y) for all reals x,y, with Λb⋆(b⋆)=1, and with range the whole of Q (Assuming the Axiom of Choice, R has a Hamel basis over Q: there is B⊆R such that every real is a finite Q-linear combination of elements of B in exactly one way, and each basis vector carries a well-defined Q-linear coefficient map, claims 1 and 4, A field is a vector space over itself, and over any subfield K⊆F every F-vector space is a K-vector space by restricting the scalars, Vector space over a field, Linear combination of a finite list, and the span span⁡(S) as the smallest linear subspace containing S).

[L2]

A function f:R→R is additive when f(x+y)=f(x)+f(y) for all reals x,y (Cauchy's functional equation f(x+y)=f(x)+f(y), and the additive functions R→R).

[L3]

There exists an irrational real, that is a real not lying in Q: the irrationals are dense in R and in particular nonempty (Both Q and R∖Q are dense in R, and every nonempty open subset of R is uncountable).

[L4]

R is a field, so a nonzero real is invertible (Complete ordered field (least-upper-bound property)).

Refutation

technique · direct
1.1

Assume the Axiom of Choice and fix a Hamel basis B of R over Q together with an element b⋆∈B; such an element exists because B spans R, which is not {0}, so B is nonempty. Put f:=Λb⋆, regarded as a function R→R.

A1L1construct
2.1

f is additive: Λb⋆(x+y)=Λb⋆(x)+Λb⋆(y) for all reals x,y is one of the properties of the coefficient map.

step 1.1L1L2
2.2

Every value of f is rational, and f(b⋆)=1.

step 1.1L1
3.1

Suppose there were a real c with f(x)=c x for every real x. Then c b⋆=f(b⋆)=1, so c≠0 and c is invertible.

step 1.1step 2.2L4
4.1

Take an irrational real θ and put x0:=c−1θ. Then f(x0)=c x0=θ, which is irrational; but every value of f is rational by step 2.2. This is impossible, so no such c exists.

step 2.2step 3.1L3L4
5.1

So f is an additive function R→R that is not of the form x↦c x for any real c, and the claim in the Statement is false.

step 2.1step 4.1discharge-construct∎

Remarks

Sources