  We study the performance of an Ising spin network for quantum reservoir
computing (QRC) in linear and non-linear memory tasks. We investigate the
extent to which quantumness enhances performance by monitoring the behaviour of
quantum entanglement, which we quantify by means of the partial transpose of
the density matrix. In the most general case where the effects of dissipation
are incorporated, our results indicate that the strength of the entanglement
advantage depends on the frequency of the input signal; the benefit of
entanglement is greater the more rapidly fluctuating the signal, whereas a
low-frequency input lends itself better to a non-entangled reservoir. This
suggests that the extent to which quantumness is beneficial is dependent on the
difficulty of the memory task.
