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Hauptverfasser: Antonio, Cedeño-Pérez Luis, Guadalup, Reyna-Castañeda Hugo, Ángeles, Sandoval-Romero María de los
Format: Preprint
Veröffentlicht: 2026
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2602.00964
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author Antonio, Cedeño-Pérez Luis
Guadalup, Reyna-Castañeda Hugo
Ángeles, Sandoval-Romero María de los
author_facet Antonio, Cedeño-Pérez Luis
Guadalup, Reyna-Castañeda Hugo
Ángeles, Sandoval-Romero María de los
contents The analytical foundations of modern probability trace back to a sequence of representation theorems that reshaped functional analysis in the twentieth century. From Fréchet identification of linear functionals with vectors in Hilbert spaces to Kakutani characterization of measures on spaces of continuous functions, each theorem reveals how linearity, duality, and measure intertwine. Following this historical and conceptual path, from Fréchet Riesz to Riesz Stieltjes, from Lp duality to Riesz Markov Kakutani, we show that expectation, distribution, conditional expectation, and the Wiener measure are analytic manifestations of a single principle of representation. Viewed through this lens, probability theory appears not merely as an extension of measure theory, but as the geometric realization of functional analysis itself: every probabilistic notion embodies an existence-and-uniqueness principle in a space of functions.
format Preprint
id arxiv_https___arxiv_org_abs_2602_00964
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Riesz to Kakutani: Representation Theorems and the Analytical Foundations of Probablility
Antonio, Cedeño-Pérez Luis
Guadalup, Reyna-Castañeda Hugo
Ángeles, Sandoval-Romero María de los
Functional Analysis
Probability
46N30, 60A99
The analytical foundations of modern probability trace back to a sequence of representation theorems that reshaped functional analysis in the twentieth century. From Fréchet identification of linear functionals with vectors in Hilbert spaces to Kakutani characterization of measures on spaces of continuous functions, each theorem reveals how linearity, duality, and measure intertwine. Following this historical and conceptual path, from Fréchet Riesz to Riesz Stieltjes, from Lp duality to Riesz Markov Kakutani, we show that expectation, distribution, conditional expectation, and the Wiener measure are analytic manifestations of a single principle of representation. Viewed through this lens, probability theory appears not merely as an extension of measure theory, but as the geometric realization of functional analysis itself: every probabilistic notion embodies an existence-and-uniqueness principle in a space of functions.
title From Riesz to Kakutani: Representation Theorems and the Analytical Foundations of Probablility
topic Functional Analysis
Probability
46N30, 60A99
url https://arxiv.org/abs/2602.00964