Quantum Annealing Systems as Reservoirs II: Quantum Channels and Computational Capacity

Reservoir computing exploits the nonlinear dynamics and high dimensionality of physical systems to continually process time-dependent signals. Recent efforts have utilized conventional quantum processors as powerful and exotic dynamical maps for quantum reservoir computing (QRC). However, one needs to continuously extract information from this computational system, and the critical role of measurement in this nascent field is relatively unexplored. Here we present a fundamental analysis of general quantum circuit reservoirs under repeated measurements, a particular case of which was considered in Part 1. We find that the presence of a quantum channel is essential to imbue the reservoir with fading memory and avoid thermalizing due to repeated measurements. The simplest description of a quantum channel in this framework is the deterministic reset of a subset of the qubits after measurement through classical control operation, which is readily implementable in quantum processors. We evaluate the fundamental information processing and memory capacity of our proposed QASAR computing framework, exemplifying the efficacy of this dephasing-resistant approach and additionally demonstrating its robust processing ability in the presence of noise and finite sampling.