Abstract
Abstract 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.
Highlights
Quantum reservoir computing (QRC) is an emerging area in the field of quantum neuromorphic computing [1, 2] that promises the potential application of near-term quantum technology to real-world problems
We explore the nature of input encodings in QRC for explicitly time-dependent tasks, and find that by virtue of quantum mechanics nonlinear input encodings are ubiquitous
We have critically examined the input procedure in quantum reservoir computing to determine the conditions on a linear encoding of the input data
Summary
Quantum reservoir computing (QRC) is an emerging area in the field of quantum neuromorphic computing [1, 2] that promises the potential application of near-term quantum technology to real-world problems. It is important to understand the nature of the dynamical map of the input data into reservoir state variables, which we refer to as the input encoding It has been shown for classical reservoirs that a nonlinear input encoding may be sufficient for task performance, even if the rest of the dynamics are fully linear [7]. In this manuscript, we explore the nature of input encodings in QRC for explicitly time-dependent tasks, and find that by virtue of quantum mechanics nonlinear input encodings are ubiquitous.
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