Implementing defuzzification operators on quantum annealers

Pourabdollah, A ORCID logoORCID: https://orcid.org/0000-0001-7737-1393, Acampora, G and Schiattarella, R, 2022. Implementing defuzzification operators on quantum annealers. In: 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy, 2022. Conference Proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). ISBN 9781665467100

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Abstract

Due to the built-in parallelism of quantum computing, there is an unexplored potential for some complex fuzzy logic computations to take the advantage of the future quantum computers. Recently, it has been introduced a novel representation of fuzzy sets and implementations of some basic fuzzy logic operators (union, intersection, alpha-cut and maximum) based on solving a Quadratic Unconstrained Binary Optimization (QUBO) problems, on a type of quantum computers known as quantum annealers. In this paper, this work is extended by presenting an implementation of centroid defuzzification on quantum annealer machines, based on binary quadratic model (BQM) but this time using Ising model. Having the basic operations and defuzzification implemented on quantum computers, this paper paves the way towards the implementation of a whole fuzzy inference engine on enhanced devices, such as quantum annealers.

Item Type: Chapter in book
Description: Paper presented at the 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy, 18-23 July 2022.
Creators: Pourabdollah, A., Acampora, G. and Schiattarella, R.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Place of Publication: Piscataway, NJ
Date: 2022
ISBN: 9781665467100
Identifiers:
Number
Type
10.1109/fuzz-ieee55066.2022.9882576
DOI
1757132
Other
Rights: © Copyright 2022 IEEE - All rights reserved.
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 10 May 2023 08:42
Last Modified: 10 May 2023 08:42
URI: https://irep.ntu.ac.uk/id/eprint/48910

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