Quantum reservoir computing (QRC) is a novel computing concept at the intersection of quantum computing and artificial neural networks. In contrast to gate-based quantum computing, the reservoir ansatz loosens the strict requirements of complete control over. Instead, a loose network of quantum systems that are connected by a random coupling topology is trained to perform computational or classification tasks.
Two great advantages come with the inherent quantumness suggested by PhotonicQRC: As a quantum machine learning ansatz, quantum input can be processed natively without the need to represent it in a classical form. Secondly, the exponential size of the Hilbert space allows to treat complex tasks with extremely small physical networks.