In recent times, quantum reservoir computing has emerged as a potential resource for time series prediction. Hence, there is a need for a flexible framework to test quantum circuits as nonlinear dynamical systems. We have developed a software package to allow for quantum reservoirs to fit a common structure, similar to that of reservoirpy which is advertised as "a python tool designed to easily define, train and use (classical) reservoir computing architectures". Our package results in simplified development and logical methods of comparison between quantum reservoir architectures. Examples are provided to demonstrate the resulting simplicity of executing quantum reservoir computing using our software package.
@article{arxiv.2401.10683,
title = {QuantumReservoirPy: A Software Package for Time Series Prediction},
author = {Stanley Miao and Ola Tangen Kulseng and Alexander Stasik and Franz G. Fuchs},
journal= {arXiv preprint arXiv:2401.10683},
year = {2024}
}