论文标题
部分可观测时空混沌系统的无模型预测
QParallel: Explicit Parallelism for Programming Quantum Computers
论文作者
论文摘要
储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。
We present a language extension for parallel quantum programming to (1) remove ambiguities concerning parallelism in current quantum programming languages and (2) facilitate space-time tradeoff investigations in quantum computing. While the focus of similar libraries in the domain of classical computing (OpenMP, OpenACC, etc.) is to divide a computation into multiple threads, the main goal of QParallel is to keep the compiler and the runtime system from introducing parallelism-inhibiting dependencies, e.g., through reuse of qubits in automatic qubit management. We describe the syntax and semantics of the proposed language extension, implement a prototype based on Q#, and present several examples and use cases to illustrate its performance benefits. Moreover, we introduce a tool that guides programmers in the placement of parallel regions by identifying the subroutines that profit most from parallelization, which is especially useful if the programmer's knowledge of the source code is limited. Support for QParallel can be added to any multithreading library and language extension, including OpenMP and OpenACC.