Predicting three-dimensional chaotic systems with four qubit quantum systems.

ABSTRACT: Reservoir computing (RC) is among the most promising approaches for AI-based prediction models of complex systems. It combines superior prediction performance with very low CPU-needs for training. Recent results demonstrated that quantum systems are also well-suited as reservoirs in RC. Due to the exponential growth of the Hilbert space dimension obtained by increasing the number of quantum elements small quantum systems are already sufficient for time series prediction. Here, we demonstrate that three-dimensional systems can already well be predicted by quantum reservoir computing with a quantum reservoir consisting of the minimal number of qubits necessary for this task, namely four. This is achieved by optimizing the encoding of the data, using spatial and temporal multiplexing and rece

SUBMITTER: Steinegger J 

PROVIDER: S-EPMC11842815 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature