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Towards probabilistic partial metric spaces: Diagonals between distance distributions

机译:走向概率局部度量空间:距离分布之间的对角线

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摘要

The quantale of distance distributions is of fundamental importance for understanding probabilistic metric spaces as enriched categories. Motivated by the categorical interpretation of partial metric spaces, we are led to investigate the quantaloid of diagonals between distance distributions, which is expected to establish the categorical foundation of probabilistic partial metric spaces. Observing that the quantale of distance distributions w.r.t. an arbitrary continuous t-norm is non-divisible, we precisely characterize diagonals between distance distributions, and prove that one-step functions are the only distance distributions on which the set of diagonals coincides with the generated down set. (C) 2018 Elsevier B.V. All rights reserved.
机译:距离分布的定量对于将概率度量空间理解为丰富的类别至关重要。基于对部分度量空间的分类解释的激励,我们被引导研究距离分布之间的对角线的量子,这有望为概率部分度量空间建立分类基础。观察到距离分布的数量w.r.t.任意连续的t范数是不可分割的,我们精确地描述了距离分布之间的对角线,并证明了一步函数是唯一的对角线集合与生成的向下集合重合的距离分布。 (C)2018 Elsevier B.V.保留所有权利。

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