Abstract
On 1936, Birkhoff and von Newmann proposed the introduction of a “quantum logic”, as the lattice of quantum mechanical proposition which is not distributive and also not a Boolean. Seven years later, Mackey tried to provide a set of axioms for the propositional system to predict of the outcome set of experiments. He indicated that the system is an orthocomplemented partially ordered set. Physical complex systems can be modeled by using linguistic variables which are variables whose values may be expressed in terms of a specific natural or artificial language, for example \(\mathbb {L}\)= {very less young; less young; young; more young; very young; very very young ...}. In language of hedge algebra (\(\mathbb{H}\mathbb{A}\)), \(\mathbb {L}\) set which is generated from \(\mathbb{H}\mathbb{A}\) is the POSET (partial order set). In this paper, we introduce a quantum logic \(\ell \) to assert that, let \(\bot \) be the orthocomplementation map \(\bot : \ell \rightarrow \ell \), all \(\clubsuit , \spadesuit \in \bot \) must satisfy the following conditions:
-
\((\clubsuit ^\bot )^\bot =\clubsuit \)
-
If \(\spadesuit \le \clubsuit \) then \(\clubsuit ^\bot \le \spadesuit ^\bot \)
-
The greatest lower bound \(\clubsuit \vee \clubsuit ^\bot \in \ell \) and the least upper bound \(\clubsuit \wedge \clubsuit ^\bot \in \ell \)
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Birkhoff, G., von Neumann, J.: The logic of quantum mechanics. Ann. Math. 37(4), 823–843 (1936)
Caarvalho, J.: On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in social sciences. Fuzzy Sets Syst. 214, 6–19 (2013)
Deng, J., Deng, Y.: QZNs: quantum z-numbers. arXiv:2104.05190 (2021)
Dvure\(\check{c}\)enskij, A.: Gleason’s Theorem and Its Applications. Mathematics and its Applications. Springer, Heidelberg (1993). https://doi.org/10.1007/978-94-015-8222-3
Engesser, K., Gabbay, D.M., Lehmann, D.: Handbook of Quantum Logic and Quantum Structures. Elsevier Science (2009)
Frias, M., Filiberto Y., Nápoles, G., Vahoof, K., Bello, R.: Fuzzy cognitive maps reasoning with words: an ordinal approach. In: ISFUROS (2017)
Glykas, M.: Fuzzy Cognitive Maps, Advances in Theory, Tools and Applications. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-03220-2
Van Han, N., Hao, N.C., Vinh, P.C.: Toward aggregating fuzzy graphs a model theory approach. In: Vinh, P.C., Rakib, A. (eds.) ICCASA/ICTCC -2019. LNICST, vol. 298, pp. 215–222. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-34365-1_17
Van Han, N., Vinh, P.C.: Modeling with words based on hedge algebra. In: Cong Vinh, P., Alagar, V. (eds.) ICCASA/ICTCC -2018. LNICST, vol. 266, pp. 211–217. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-06152-4_18
Van Han, N., Vinh, P.C.: Toward modeling and reasoning with words based on hedge algebra. EAI Endors. Trans. Context-Aware Syst. Appl. 5(15), e5 (2018)
Han, N.V., Vinh, P.C., Phung, B.M., Dan, T.N.: Hidden pattern: toward decision support fuzzy systems. In: Cong Vinh, P., Rakib, A. (eds.) ICCASA 2021. LNICST, vol. 409, pp. 71–76. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-93179-7_6
Ho, N.C., Long, N.V.: Fuzziness measure on complete hedge algebras and quantifying semantics of terms in linear hedge algebras. Fuzzy Sets Syst. 158(4), 452–471 (2007)
Ho, N.C., Son, T.T., Khang, T.D., Viet, L.X.: Fuzziness measure, quantified semantic mapping and interpolative method of approximate reasoning in medical expert systems. J. Comput. Sci. Cybern. 18(3), 237–252 (2002)
Ho, N.C., Wechler, W.: Hedge algebras: an algebraic approach to structure of sets of linguistic truth values. Fuzzy Sets Syst. 35(3), 281–293 (1990)
Zadeh, L.A.: The concept of a linguistic variable and its applications to approximate reasoning. Inf. Sci. 8(3), 199–249 (1975)
Zadeh, L.A.: Computing with Words - Principal Concepts and Ideas. Studies in Fuzziness and Soft Computing, Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-27473-2
Mackey, G.W.: Mathematical Foundations of Quantum Mechanics. W.A Benjamin (1963)
Mannucci, M.A.: Quantum fuzzy sets: blending fuzzy set theory and quantum computation. arXiv:cs/0604064 (2006)
Nguyen, C.-H., Huynh, V.-N.: An algebraic approach to linguistic hedges in Zadeh’s fuzzy logic. Fuzzy Sets Syst. 129(2), 229–254 (2002)
Papageorgiou, E.I.: Fuzzy Cognitive Maps for Applied Science and Engineering From Fundamentals to Extensions and Learning Algorithms. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-39739-4
Pykacz, J.: Quantum Physics, Fuzzy Sets and Logic: Steps Towards a Many-Valued Interpretation of Quantum Mechanics. SpringerBriefs in Physics, Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-319-19384-7
Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybern. 3(1), 28–44 (1973)
Zadeh, L.A., Kacprzyk, J.: Computing with Word in Information Intelligent System 1. Springer, Heidelberg (1999). https://doi.org/10.1007/978-3-7908-1873-4
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Van Han, N., Vinh, P.C. (2023). Modeling with Words: Steps Towards a Fuzzy Quantum Logic. In: Phan, C.V., Nguyen, T.D. (eds) Nature of Computation and Communication. ICTCC 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 473. Springer, Cham. https://doi.org/10.1007/978-3-031-28790-9_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-28790-9_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-28789-3
Online ISBN: 978-3-031-28790-9
eBook Packages: Computer ScienceComputer Science (R0)