Non-existence of measurable solutions of certain functional equations via probabilistic approaches
Pith reviewed 2026-05-24 13:41 UTC · model grok-4.3
The pith
No measurable solutions exist for f(x) + g(y) = h(x,y) when h is Borel measurable and tied to uniform or Cauchy distribution characterizations.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
If h is a Borel measurable function associated with characterizations of the uniform or Cauchy distributions, then there is no measurable solutions of the equation f(x) + g(y) = h(x,y). The proof uses a characterization of the Dirac measure and it is also applicable to the arctan equation.
What carries the argument
Characterization of the Dirac measure, used to obtain a contradiction from the assumption of measurable f and g.
If this is right
- No measurable solutions exist when h comes from uniform distribution characterizations.
- No measurable solutions exist when h comes from Cauchy distribution characterizations.
- The arctan functional equation likewise admits no measurable solutions.
- Probabilistic characterizations can be turned into non-existence proofs for additive equations under measurability constraints.
Where Pith is reading between the lines
- Similar contradictions may appear for other distribution characterizations that produce Dirac-like concentration properties.
- The result separates the measurable and non-measurable regimes for additive representations of probability identities.
- Any search for solutions would need to invoke non-measurable functions, which typically require the axiom of choice.
Load-bearing premise
The given h must be Borel measurable and must arise specifically from the characterizations of the uniform or Cauchy distributions.
What would settle it
An explicit construction of Borel measurable f and g satisfying f(x) + g(y) = h(x,y) for any such h would falsify the non-existence result.
read the original abstract
This paper deals with functional equations in the form of $f(x) + g(y) = h(x,y)$ where $h$ is given and $f$ and $g$ are unknown. We will show that if $h$ is a Borel measurable function associated with characterizations of the uniform or Cauchy distributions, then there is no measurable solutions of the equation. Our proof uses a characterization of the Dirac measure and it is also applicable to the arctan equation.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper claims that for the functional equation f(x) + g(y) = h(x,y) with h Borel measurable and associated with characterizations of the uniform or Cauchy distributions, there are no measurable solutions f,g. The argument relies on a characterization of the Dirac measure to derive a contradiction and is stated to apply also to the arctan equation.
Significance. If the central link between the given h and the distributional characterizations can be made rigorous, the probabilistic approach via Dirac-measure characterization would offer a compact non-existence proof for a class of functional equations arising in probability characterizations; this could be of interest in the intersection of functional equations and probability theory.
major comments (2)
- [Abstract / Introduction] The central claim requires that the supplied Borel h 'arises specifically from' the uniform or Cauchy characterizing equations so that the functional equation forces the measure to be Dirac. The manuscript provides no explicit construction, theorem reference, or reduction showing how those characterizations produce the particular h that triggers the Dirac step; without this link the contradiction does not follow.
- [Abstract] The arctan case is asserted to be covered by the same argument, yet no reduction or verification is supplied showing that the corresponding h satisfies the required association with a distributional characterization.
Simulated Author's Rebuttal
We thank the referee for the careful reading and the constructive major comments. The points raised correctly identify gaps in the presentation of the link between the distributional characterizations and the specific h, as well as the arctan case. We address each comment below and will revise the manuscript to supply the missing explicit constructions and reductions.
read point-by-point responses
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Referee: [Abstract / Introduction] The central claim requires that the supplied Borel h 'arises specifically from' the uniform or Cauchy characterizing equations so that the functional equation forces the measure to be Dirac. The manuscript provides no explicit construction, theorem reference, or reduction showing how those characterizations produce the particular h that triggers the Dirac step; without this link the contradiction does not follow.
Authors: We agree that the manuscript does not contain an explicit construction, theorem reference, or reduction showing how the uniform and Cauchy characterizations produce the Borel measurable h that triggers the Dirac-measure step. In the revised version we will add a short preliminary section (or subsection of the introduction) that supplies this link: we will state the relevant characterizing equations, derive the associated h(x,y), and verify that the functional equation then forces the measure to be Dirac, yielding the desired contradiction. revision: yes
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Referee: [Abstract] The arctan case is asserted to be covered by the same argument, yet no reduction or verification is supplied showing that the corresponding h satisfies the required association with a distributional characterization.
Authors: The referee correctly notes that the abstract asserts coverage of the arctan equation without supplying a reduction or verification. We will revise the manuscript to include a brief paragraph (or appendix note) that reduces the arctan equation to the same framework, confirming that its h satisfies the association with a distributional characterization and is therefore covered by the Dirac-measure argument. revision: yes
Circularity Check
No significant circularity detected; proof applies external Dirac characterization independently
full rationale
The derivation applies an external characterization of the Dirac measure to the functional equation f(x) + g(y) = h(x,y) where h is given as Borel measurable and associated with uniform/Cauchy characterizations. No self-definitional reduction, fitted-input prediction, or load-bearing self-citation chain appears; the Dirac step is invoked as an independent probabilistic tool rather than derived from the paper's own inputs or prior author work. The arctan applicability is likewise presented as an extension of the same external method. The result is therefore self-contained against external benchmarks.
Axiom & Free-Parameter Ledger
Lean theorems connected to this paper
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IndisputableMonolith/Cost/FunctionalEquation.leanwashburn_uniqueness_aczel unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
if h is a Borel measurable function associated with characterizations of the uniform or Cauchy distributions, then there is no measurable solutions of the equation. Our proof uses a characterization of the Dirac measure
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IndisputableMonolith/Foundation/AbsoluteFloorClosure.leanabsolute_floor_iff_bare_distinguishability unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
Lemma 2.1 (Characterization of Dirac measures). If X and Y are independent, and, X + Y and Y are independent, then, Y is a constant a.s.
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
Reference graph
Works this paper leans on
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[1]
Barry C. Arnold, Some characterizations of the Cauchy distribution , Australian Journal of Statistics 21 (1979), 166–169
work page 1979
-
[2]
Borislav Crstici, Ioan Muntean, and Neculae Vornicescu, General solution of the arct- angent functional equation , L’Analyse Num´ erique et de Th´ eorie de l’Approximation12 (1983), 113–123
work page 1983
-
[3]
Lih-Yuan Dengand and E. Olusegun George, Some characterizations of the uniform distribution with applications to random number generatio n, Annals of Institute of Sta- tistical Mathematics 44 (1992), 379–385
work page 1992
-
[4]
Wis- senschaftliche Zeitschrift
Helmut Kiesewetter, Uber die arc tan-Funktionalgleichung, ihre mehrdeutigen, steti- gen Losungen und eine nichtstetige Gruppe , Friedrich-Schiller-Universitat Jena. Wis- senschaftliche Zeitschrift. Naturwissenschaftliche Rei he 14 (1965), 417–421
work page 1965
-
[5]
Laszlo Losonczi, Local solutions of functional equations , Druˇ sstvo Matematiˇ cara i Fiziˇ cara S. R. Hrvatske. Glasnik Matematiˇ cki. Serija III25(45) (1990), no. 1, 57–67
work page 1990
-
[6]
Michael Mania, A probabilistic method of solving Lobachevsky’s functiona l equation, 95 (2021), no. 2, 237–243
work page 2021
- [7]
-
[8]
Walter Rudin, Real and complex analysis , 3rd ed., McGraw-Hill, 1987
work page 1987
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[9]
Sergey N. Smirnov, A probabilistic note on the Cauchy functional equation , Aequationes Mathematicae 93 (2019), 445–449. School of General Education, Shinshu University Current address: Department of Mathematics, Faculty of Science, Shizuoka U niversity Email address : okamura.kazuki@shizuoka.ac.jp
work page 2019
discussion (0)
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