As we continue to find applications where the currently available noisy devices exhibit an advantage over their classical counterparts, the efficient use of quantum resources is highly desirable. The notion of quantum autoencoders was proposed as a way for the compression of quantum information to reduce resource requirements. Here, we present a strategy to design quantum autoencoders using evolutionary algorithms for transforming quantum information into lower-dimensional representations. We successfully demonstrate the initial applications of the algorithm for compressing different families of quantum states. In particular, we point out that using a restricted gate set in the algorithm allows for efficient simulation of the generated circuits. This approach opens the possibility of using classical logic to find low representations of quantum data, using fewer computational resources.
翻译:当我们继续发现现有噪音装置比古典对等装置具有优势的应用程序时,高效使用量子资源是非常可取的。 量子自动计算器的概念被提出来作为压缩量子信息以减少资源需求的一种方式。 在这里,我们提出了一个战略,用进化算法设计量子自动计算器,将量子信息转化为低维表示法。 我们成功地展示了压缩量子国家不同家族的算法的初始应用。 特别是,我们指出,使用算法中设定的限量门可以有效地模拟产生的电路。 这种方法开启了利用传统逻辑找到量子数据低表示法的可能性, 使用较少的计算资源。