Quantum operations with indefinite causal order (ICO) represent a framework in quantum information processing where the relative order between two events can be indefinite. In this paper, we investigate whether sensing and computation, two canonical tasks in quantum information processing, can be carried out within the ICO framework. We propose a scheme for integrated sensing and computation that uses the same quantum state for both tasks. The quantum state is represented as an agent that performs state observation and learns a function of the state to make predictions via a parametric model. Under an ICO operation, the agent experiences a superposition of orders, one in which it performs state observation and then executes the required computation steps, and another in which the agent carries out the computation first and then performs state observation. This is distinct from prevailing information processing and machine intelligence paradigms where information acquisition and learning follow a strict causal order, with the former always preceding the latter. We provide experimental results and we show that the proposed scheme can achieve small training and testing losses on a representative task in magnetic navigation.

翻译：不确定因果序（ICO）量子操作代表了量子信息处理中的一个框架，其中两个事件之间的相对顺序可以是不确定的。本文研究了量子信息处理中的两项典型任务——传感与计算——是否能在ICO框架内执行。我们提出了一种集成传感与计算的方案，该方案使用同一量子态完成这两项任务。该量子态被表示为一个智能体，它执行状态观测并通过参数化模型学习状态函数以进行预测。在ICO操作下，该智能体会经历顺序的叠加：一种顺序是智能体先执行状态观测，随后执行所需的计算步骤；另一种顺序则是智能体先进行计算，再进行状态观测。这区别于当前主流的信息处理与机器智能范式，在后者中信息获取与学习遵循严格的因果顺序，且前者总是先于后者发生。我们提供了实验结果，并表明所提出的方案能在磁导航代表性任务上实现较小的训练与测试损失。