Constructive Analysis in Infinitely many variables
Tepper L. Gill, Gogi R. Pantsulaia, Woodford W. Zachary

TL;DR
This paper develops a topological framework for constructing Lebesgue and Gaussian measures in infinite-dimensional spaces, extending classical analysis tools to infinitely many variables with applications to PDEs.
Contribution
It introduces a measure construction on infinite-dimensional spaces using a topological approach, connecting von Neumann's tensor product theory with measure theory and Fourier analysis.
Findings
Constructed a canonical $L^2$ space on $ ^ y$ with a $\s$-finite measure
Extended Fubini's theorem and Young's inequality to infinite-dimensional Banach spaces
Provided examples of PDEs in infinite-dimensional phase spaces
Abstract
In this paper we investigate the foundations for analysis in infinitely-many (independent) variables. We give a topological approach to the construction of the regular -finite Kirtadze-Pantsulaia measure on (the usual completion of the Yamasaki-Kharazishvili measure), which is an infinite dimensional version of the classical method of constructing Lebesgue measure on (see \cite{YA1}, \cite{KH} and \cite{KP2}). First we show that von Neumann's theory of infinite tensor product Hilbert spaces already implies that a natural version of Lebesgue measure must exist on . Using this insight, we define the canonical version of , which allows us to construct Lebesgue measure on and analogues of Lebesgue and Gaussian measure for every separable Banach space with a Schauder basis. When is a Hilbert space and is…
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Taxonomy
TopicsStochastic processes and financial applications · advanced mathematical theories · Mathematical Dynamics and Fractals
