Measure, Randomness and Sublocales
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@MISC{Simpson_measure,randomness,
author = {Alex Simpson},
title = {Measure, Randomness and Sublocales},
year = {}
}
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Abstract
This paper investigates aspects of measure and randomness in the context of locale theory (point-free topology). We prove that every measure (σ-continuous valuation) µ, on the σ-frame of opens of a fitted σ-locale X, extends to a measure on the lattice of all σ-sublocales of X (Theorem 1). Furthermore, when µ is a finite measure with µ(X) = M, the σ-locale X has a smallest σ-sublocale of measure M (Theorem 2). In particular, when µ is a probability measure, X has a smallest σ-sublocale of measure 1. All σ prefixes can be dropped from these statements whenever X is a strongly Lindelöf locale, as is the case in the following applications. When µ is Lebesgue measure on Euclidean space R n, Theorem 1 produces an isometry-invariant measure that, via the inclusion of the powerset P(R n) in the lattice of sublocales, assigns a weight to every subset of R n. (Contradiction is avoided because disjoint subsets need not be disjoint as sublocales.) When µ is the uniform probability measure on Cantor space {0, 1} ω, the smallest measure-1 sublocale, given by Theorem 2, provides a canonical locale of random sequences, where randomness means that all probabilistic laws (measure-1 properties) are satisfied. 1.
Keyphrases
smallest sublocale locale theory measure-1 property probabilistic law probability measure uniform probability measure canonical locale measure-1 sublocale finite measure following application continuous valuation cantor space fitted locale lebesgue measure random sequence disjoint subset point-free topology lindel locale isometry-invariant measure euclidean space
