Reservoir Computing Using Measurement-Controlled Quantum Dynamics

Modern digital computers can solve virtually any computational problem. However, to accomplish a computational task of arbitrary complexity, they may require impracticably large resources such as time and memory. To resolve this challenge, unconventional [1,2] and neuromorphic [3-10] computing were proposed as the new methods of computer engineering, where elements of a computer mimic the operation of a biological brain relying on physical and chemical processes [11,12]. While neuromorphic computers may not be as universal as the traditional digital ones, they can solve certain practically important problems with feasible accuracy using just a small amount of computational resources and energy needed by a high-performance computer tasked with the same problem. Neuromorphic computers are also inherently scalable, parallel and allow for collocation of data processing and memory [9]. Similarly to a biological brain, they also operate only when input data are available and mimic the randomness of the firing of biological neurons, thus helping save energy and decrease the overall cost of computations [13,14].