利用流生成单向计算：忽略解释的流保持重写
Generating one-way computations with flow: flow-preserving rewriting that ignores the interpretation
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中文总结 AI 辅助
研究单向计算中流保持重写，不局限于保留解释。核心方法是特定重写规则，主要贡献是仅三个流保持重写规则就能从平凡图生成任意带流图，可用于相关软件测试及量子机器学习。
中文摘要 AI 辅助
单向模型是量子计算通用模型，由对纠缠资源态的连续自适应单比特测量驱动。测量是非确定性的，但满足“流”条件时可通过修改后续测量变为确定性。流属性有助于单向计算与电路的高效转换。现有方法用于编译或优化，本文考虑不保留解释的流保持重写，用于软件测试及量子机器学习，证明三个重写规则可生成任意带流图。
英文摘要
The one-way model is a universal model of quantum computation, driven by successive adaptive single-qubit measurements on an entangled resource state. Measurements are non-deterministic, yet if the computation satisfies one of several related families of conditions known as 'flows', the computation can be made deterministic overall by modifying later measurements depending on the outcomes of earlier ones. Flow properties also enable efficient translation from one-way computations to circuits, motivating research into rewriting one-way computations while preserving the existence of flow. Existing approaches to flow-preserving rewriting are used for compilation or optimisation and preserve both the interpretation and the existence of flow. Here, we broaden our perspective to consider flow-preserving rewriting that does not necessarily preserve the interpretation, with applications to creating test instances for software that works with flow, as well as to generating ansätze for quantum machine learning. We show that a family of just three flow-preserving rewrite rules suffices to generate any diagram with flow from a trivial diagram with the desired number of inputs and outputs. This rule set is nearly the same as the complete set of flow- and interpretation-preserving rewrite rules for one-way computations in which all measurements are Pauli; and just a small subset of the flow- and interpretation-preserving rewrite rules for arbitrary measurements.
