Anna Frolova

A numerical study builds a reservoir-computing system from three-level quantum memristors on a trapped ion, using Born-rule nonlinearity, quantum coherences and feedback memory to process classical time series. Two coupled quantum memristors with two chip passes keep test MSE below 10^-2 on monomial targets x^d up to d=100, at the cost of raising readout weights to 50, while classical echo state networks fail beyond about d=40 even at 2000 nodes. On memory-dominated tasks such as NARMA10, the reservoir only matches minimal classical networks.

A numerical study builds a reservoir-computing system from three-level quantum memristors on a trapped ion, using Born-rule nonlinearity, quantum coherences and feedback memory to process classical time series. Two coupled quantum memristors with two chip passes keep test MSE below 10^-2 on monomial targets x^d up to d=100, at the cost of raising readout weights to 50, while classical echo state networks fail beyond about d=40 even at 2000 nodes. On memory-dominated tasks such as NARMA10, the reservoir only matches minimal classical networks.