Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Annals of the Japan Association for Philosophy of Science

Quantum Logic in the Framework of Linear Logic

Akira Oide

Published Jan 1, 1996• 1 citation
Publisher
DOI
10.4288/jafpos1956.9.35

Related papers

Quantum logic and linear logic

Leopoldo Rom�n

International Journal of Theoretical Physics•Jun 1, 1994•17 citations

What has Operational Quantum Logic to do with Linear Logic

Sonja Smets

•Jan 1, 2002•1 citation

Quantum Intelligent Systems: A Hybrid Quantum-Logic Framework Integrating Physical, Control, and Cognitive Layers Author: Dr. Siamak Noorolahi Affiliation: SBMU Abstract Traditional intelligent systems are built upon the classical von Neumann architecture, which relies on deterministic logic and linear hierarchical processing. This paradigm faces significant limitations when addressing high-dimensional, non-linear, and stochastic environments. This paper proposes a novel framework for Quantum Intelligent Systems (QIS) based on Hybrid Quantum Logic. We introduce a multi-layered architecture comprising the Physical Layer, the Control Layer, and the Cognitive Layer, interconnected through quantum phenomena such as superposition and entanglement. Unlike classical systems where layers are strictly sequential, our framework treats the system as a unified quantum field where information processing, actuation, and cognition occur through the controlled collapse of a system-wide wave function. This approach provides a theoretical basis for achieving unprecedented levels of autonomy and strategic adaptability in complex robotic and autonomous systems. Keywords: Quantum Intelligent Systems (QIS), Hybrid Quantum Logic, Cognitive Layer, Entanglement-based Control, Wave Function Collapse in Decision Making.

Noorolahi

•Oct 7, 2026•0 citations

Quantum Logic as an Extension of Classical Logic

Sergio Bernini

Springer eBooks•Jan 1, 1981•3 citations

On the probabilistic logical modelling of quantum and geometrically-inspired IR

Fabrizio Smeraldi, Miguel Martinez-Alvarez, Ingo Frommholz +1 more

Abstract. Information Retrieval approaches can mostly be classed into probabilistic, geometric or logic-based. Recently, a new unifying framework for IR has emerged that integrates a probabilistic description within a geometric framework, namely vectors in Hilbert spaces. The geometric model leads naturally to a predicate logic over linear subspaces, also known as quantum logic. In this paper we show the relation between this model and classic concepts such as the Generalised Vector Space Model, highlighting similarities and differences. We also show how some fundamental components of quantum-based IR can be modelled in a descriptive way using a well-established tool, i.e. Probabilistic Datalog. 1

IIR eBooks•Jan 1, 2011•1 citation

Quantum Logic in Algebraic Approach

Miklós Rédei

Springer eBooks•Jan 1, 1998•241 citations
Quantum Intelligent Systems: A Hybrid Quantum-Logic Framework Integrating Physical, Control, and Cognitive Layers Author: Dr. Siamak Noorolahi Affiliation: SBMU Abstract Traditional intelligent systems are built upon the classical von Neumann architecture, which relies on deterministic logic and linear hierarchical processing. This paradigm faces significant limitations when addressing high-dimensional, non-linear, and stochastic environments. This paper proposes a novel framework for Quantum Intelligent Systems (QIS) based on Hybrid Quantum Logic. We introduce a multi-layered architecture comprising the Physical Layer, the Control Layer, and the Cognitive Layer, interconnected through quantum phenomena such as superposition and entanglement. Unlike classical systems where layers are strictly sequential, our framework treats the system as a unified quantum field where information processing, actuation, and cognition occur through the controlled collapse of a system-wide wave function. This approach provides a theoretical basis for achieving unprecedented levels of autonomy and strategic adaptability in complex robotic and autonomous systems. Keywords: Quantum Intelligent Systems (QIS), Hybrid Quantum Logic, Cognitive Layer, Entanglement-based Control, Wave Function Collapse in Decision Making.
Abstract. Information Retrieval approaches can mostly be classed into probabilistic, geometric or logic-based. Recently, a new unifying framework for IR has emerged that integrates a probabilistic description within a geometric framework, namely vectors in Hilbert spaces. The geometric model leads naturally to a predicate logic over linear subspaces, also known as quantum logic. In this paper we show the relation between this model and classic concepts such as the Generalised Vector Space Model, highlighting similarities and differences. We also show how some fundamental components of quantum-based IR can be modelled in a descriptive way using a well-established tool, i.e. Probabilistic Datalog. 1