We introduce the category of information structures, whose objects are suitable diagrams of measurable sets that encode the possible outputs of a given family of observables and their mutual relationships of refinement; they serve as mathematical models of contextuality in classical and quantum settings. Each information structure can be regarded as a ringed site with trivial topology; the structure ring is generated by the observables themselves and its multiplication corresponds to joint measurement. We extend Baudot and Bennequin's definition of information cohomology to this setting, as a derived functor in the category of modules over the structure ring, and show explicitly that the bar construction gives a projective resolution in that category, recovering in this way the cochain complexes previously considered in the literature. Finally, we study the particular case of a one-parameter family of coefficients made of functions of probability distributions. The only 1-cocycles are Shannon entropy or Tsallis $\alpha$-entropy, depending on the value of the parameter.
翻译:我们引入了信息结构类别,其对象为可计量数据集的合适图表,该图表将特定系列的可观测物体的可能产出及其相互改进的关系编码;它们作为古典和量子环境中背景质量的数学模型;每种信息结构可被视为一个环状地点,具有微不足道的地形学;结构环由可观测物体本身产生,其乘数与联合测量相对应;我们将Baudot和Bennequin对信息共生学的定义扩展至这一环境,作为模块类别中的衍生真菌,置于结构环之上,并明确表明条形构造在这一类别中提供了一种预测性分辨率,从而以这种方式恢复了以前在文献中审议过的连锁综合体;最后,我们研究了由概率分布函数生成的单数系列系数的特定案例;只有香农的酶或Tsallis $\alpha$-entropy,视参数的价值而定。