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Evolutionary Approach to Quantum and Reversible Circuits Synthesis

机译:量子与可逆电路综合的进化方法

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The paper discusses the evolutionary computation approach to the problem of optimal synthesis of Quantum and Reversible Logic circuits. Our approach uses standard Genetic Algorithm (GA) and its relative power as compared to previous approaches comes from the encoding and the formulation of the cost and fitness functions for quantum circuits synthesis. We analyze new operators and their role in synthesis and optimization processes. Cost and fitness functions for Reversible Circuit synthesis are introduced as well as local optimizing transformations. It is also shown that our approach can be used alternatively for synthesis of either reversible or quantum circuits without a major change in the algorithm. Results are illustrated on synthesized Margolus, Toffoli, Fredkin and other gates and Entanglement Circuits. This is for the first time that several variants of these gates have been automatically synthesized from quantum primitives.
机译:本文讨论了量子计算和可逆逻辑电路最佳综合问题的进化计算方法。我们的方法使用标准的遗传算法(GA),与以前的方法相比,其相对功效来自量子电路合成的成本和适应度函数的编码和公式化。我们分析了新的运算符及其在综合和优化过程中的作用。引入了可逆电路综合的成本和适应度函数以及局部优化转换。还表明,我们的方法可以替代性地用于可逆或量子电路的合成,而无需对该算法进行重大更改。在合成的Margolus,Toffoli,Fredkin和其他门和纠缠电路中说明了结果。这是第一次从量子图元自动合成这些门的几种变体。

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