Nonlinear input transformations are ubiquitous in quantum reservoir computing
Nonlinear input transformations are ubiquitous in quantum reservoir computing
复制标题
非线性输入变换在量子存储计算中无处不在
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Thomas A. Ohki
中科院分区：
文献类型：
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作者：
Luke C. G. Govia;G. Ribeill;Graham E. Rowlands;Thomas A. Ohki
量子库计算的新兴计算范式展示了近期、中等噪声规模量子处理器的有吸引力的用途。为了了解量子存储计算的潜在能力和用例，有必要定义一个概念框架来分离其组成部分并确定它们对性能的影响。在这份手稿中，我们利用这样的框架来隔离当代量子存储计算方案的输入编码组件。我们发现，在大多数方案中，输入编码对输入数据实现了非线性变换。由于已知非线性是油藏计算中的关键计算资源，因此这对进一步输入后处理的必要性和功能提出了质疑。我们的研究结果将影响未来量子储层的设计，以及结果的解释和拟议设计之间的公平比较。
The nascent computational paradigm of quantum reservoir computing presents an attractive use of near-term, noisy-intermediate-scale quantum processors. To understand the potential power and use cases of quantum reservoir computing, it is necessary to define a conceptual framework to separate its constituent components and determine their impacts on performance. In this manuscript, we utilize such a framework to isolate the input encoding component of contemporary quantum reservoir computing schemes. We find that across the majority of schemes the input encoding implements a nonlinear transformation on the input data. As nonlinearity is known to be a key computational resource in reservoir computing, this calls into question the necessity and function of further, post-input, processing. Our findings will impact the design of future quantum reservoirs, as well as the interpretation of results and fair comparison between proposed designs.