Quantum-Cognitive Artificial Neural Networks

Ivan S. Maksymov

Davide Pastorello

Milan Maksimovic, Anna Bohdanets, Immaculate Dadiso Motsi-Omoijiade +2 more

Abstract Prior work has demonstrated that incorporating well-known quantum-physical tunnelling probability into artificial neural network models effectively captures important nuances of human cognition and perception, particularly in the recognition of ambiguous objects and sentiment analysis. In this paper, we employ novel tunnelling-based artificial neural networks and assess their effectiveness in distinguishing customised images of military and civilian vehicles, as well as sentiment, using a proprietary military-specific vocabulary. We show that quantum tunnelling neural networks can enhance multimodal AI applications in battlefield scenarios, particularly within human-operated drone warfare contexts, imbuing AI with certain traits of human reasoning.

Sanjay Gupta, Royce K. P. Zia

Carlos Pedro Gonçalves

A future quantum technological infrastructure demands the development of quantum cyber-physical-cognitive systems, merging quantum artificial intelligence, quantum robotics and quantum information and communication technologies. To support such a development, the current work introduces a new interpretation of quantum mechanics, grounded on a link between quantum computer science, systems science and field-based computation. This new interpretation is applied to quantum artificial neural networks, with examples implemented experimentally on IBM's five qubit transmon bowtie chip, accessed via cloud using IBM Q Experience, illustrating how quantum neural computing can be implemented on actual quantum computers. A new form of quantum neural machine learning, based on a quantum optimization of a conditional utility function is also introduced and applied to quantum robotics, where a quantum robot, characterized by an interface and a multilayer quantum artificial neural network, interacts with a quantum target, changing the target's dynamics adaptively, based upon the quantum optimization dynamics, computing the optima for a performance measure and changing the target's dynamics accordingly.

Huaixin Cao, Feilong Cao, Dianhui Wang