Work

Realising and compressing quantum circuits with quantum reservoir computing

Year: 2021

Type: article

Abstract: Quantum computers require precise control over parameters and careful engineering of the underlying physical system. In contrast, neural networks have evolved to tolerate imprecision and inhomogeneity. Here, using a reservoir computing architecture we show how a random network of quantum nodes can be used as a robust hardware for quantum computing. It induces quantum operations by optimising only a single layer of quantum nodes, a key advantage over the traditional neural networks where many layers of neurons have to be optimised. We demonstrate how a single network can induce different quantum gates, including a universal gate set. Moreover, we show that sequences of multiple quantum gates in quantum circuits can be compressed with a single operation, greatly reducing the operation time and complexity. As the key resource is a random network of nodes, with no specific topology or structure, this architecture is a hardware friendly alternative paradigm for quantum computation.

Source: Communications Physics

DOI: 10.1038/s42005-021-00606-3

Authors: Sanjib Ghosh, Tanjung Krisnanda, Tomasz Paterek, Timothy C. H. Liew