Quantum inference engine: an architecture for quantum artificial intelligence

Nan Wu; Fangming Song; Wenxuan Zhang; Xiangdong Li

doi:10.1117/12.3022579

7 June 2024 Quantum inference engine: an architecture for quantum artificial intelligence

Nan Wu, Fangming Song, Wenxuan Zhang, Xiangdong Li

Proceedings Volume 13028, Quantum Information Science, Sensing, and Computation XVI; 130280A (2024) https://doi.org/10.1117/12.3022579
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

The development of quantum artificial intelligence (QAI) may lead a new computing revolution. This paper studies a model of quantum inference engine (QIE), which is a novel architecture designed to enhance quantum artificial intelligence by leveraging quantum principles. It discusses a role of the quantum superposition and entanglement in the transition from classical to quantum computational models, which surpasses the classical inference engines. The details of QIE’s structure is provided, from the quantum knowledge base to the inference mechanisms, demonstrating the capacity in the parallel processing and complex probabilistic reasoning. This research outlines the significant advancements in computational inference with the quantum technologies, especially in the era of the Noisy Intermediate-Scale Quantum (NISQ). The QIE shows its improved efficiency, scalability, and accuracy in handling intricate data and probabilistic models. The quantum inference engine will be useful for the research and applications in quantum artificial intelligence.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Nan Wu, Fangming Song, Wenxuan Zhang, and Xiangdong Li "Quantum inference engine: an architecture for quantum artificial intelligence", Proc. SPIE 13028, Quantum Information Science, Sensing, and Computation XVI, 130280A (7 June 2024); https://doi.org/10.1117/12.3022579

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available