一句话：为可测锥建立积分理论，使概率编程语言的抽样原语可在锥语义模型中获得解释，并构造线性逻辑的两个指数余单子。
可测锥此前可建模直觉主义线性逻辑与按名调用概率 PCF，并支持实数线等连续数据类型，但缺少对以锥为陪域的函数的积分理论，因而无法解释更一般概率语言（尤其按值调用与 call-by-push-value）中的抽样原语。本文把拓扑向量空间中的 Pettis 积分推广到锥上，定义了锥值函数的积分与可积锥，并以保积分线性映射为态射。作者证明由此得到的范畴是线性逻辑的模型，并构造两个指数余单子：其一基于已有的稳定可测函数概念，其二基于新提出的锥上可积解析函数概念。
Measurable cones, with linear and measurable functions as morphisms, are a model of intuitionistic linear logic and of call-by-name probabilistic PCF which accommodates "continuous data types" such as the real line. So far however, they lacked a major feature to make them a model of more general probabilistic programming languages (notably call-by-value and call-by-push-value languages): a theory of integration for functions whose codomain is a cone, which is the key ingredient for interpreting the sampling programming primitives. The goal of this paper is to develop such a theory: our definition of integrals is an adaptation to cones of Pettis integrals in topological vector spaces. We prove that such integrable cones, with integral-preserving linear maps as morphisms, form a model of Linear Logic for which we develop two exponential comonads: the first based on a notion of stable and measurable functions introduced in earlier work and the second based on a new notion of integrable analytic function on cones.