Quantum Neural Network and Soft Quantum Computing

TL;DR

This paper introduces a new paradigm called soft quantum computing, exemplified by a quantum neural network that leverages environmental decoherence and quantum discord to enable more realistic quantum artificial intelligence.

Contribution

It proposes the concept of soft quantum computing and develops a quantum neural network model that incorporates realistic neuron behavior and quantum laws for information processing.

Findings

Quantum discord indicates quantum features in the neural network.

Non-commutability of quantum operations reveals quantum effects.

The model suggests a pathway to earlier realization of quantum computers.

Abstract

A new paradigm of quantum computing, namely, soft quantum computing, is proposed for nonclassical computation using real world quantum systems with naturally occurring environment-induced decoherence and dissipation. As a specific example of soft quantum computing, we suggest a quantum neural network, where the neurons connect pairwise via the "controlled Kraus operations", hoping to pave an easier and more realistic way to quantum artificial intelligence and even to better understanding certain functioning of the human brain. Our quantum neuron model mimics as much as possible the realistic neurons and meanwhile, uses quantum laws for processing information. The quantum features of the noisy neural network are uncovered by the presence of quantum discord and by non-commutability of quantum operations. We believe that our model puts quantum computing into a wider context and inspires the hope to build a soft quantum computer much earlier than the standard one.