We present a new concept for quantum computation and algorithms along with its theoretical understanding of quantum physics. We formulates the quantum logic and cognition of mind in general as the eigen value problems with the introduction of cognitive quantum number (CNQ), which interprets that the measurement act in the quantum domain parallels a decision process in domain of logic and it translates between the two. We also described the intelligent code of mind considering its operation as quantum mechanical in nature, that helps the modeling of information processing in case of quantum computing. Synthesis and spectral response of nano-particle towards quantum dot formation is also studied.
We present a new concept for quantum computation and algorithms along with its theoretical understanding of quantum physics. We formulates the quantum logic and cognition of mind in general as the eigen value problems with the introduction of cognitive quantum number (CNQ), which interprets that the measurement act in the quantum domain parallels a decision process in domain of logic and it translates between the two. We also described the intelligent code of mind considering its operation as quantum mechanical in nature, that helps the modeling of information processing in case of quantum computing. Synthesis and spectral response of nano-particle towards quantum dot formation is also studied.
We present the new mathematical formalisms of Cognitive Quantum Number (CQN), as unified validation logic in human minds and machines. Though our theory is general, on study we concentrate in logic formation in the field of quantum computing specially for information processing in nano-scale devices. Our proposed logic not only allows us to derive the results of quantum state, but also permits their generalization of making available new techniques of logic inference, establishes a direct dynamical link between memory and processing part naturally. We consider quantum logic and cognition of mind in general as Eigen value problems. The role of molecular magnets in the field of quantum computation and mechanism for using it as qubits in the context of quantum phenomenon of spin tunneling in presence of external magnetic fields is formulated. Synthesis and spectral response of nano-particle towards quantum dot formation is also studied. We showed that the spectrum of logic operators and cognition of minds is in exact correspondence of the fundamentals alphabet of logic truth-values. The basic gate for quantum logic operations is also derived.
The conceptuality interpretation of quantum mechanics proposes that quantum entities have a conceptual nature, interacting with the material world through processes that are the physical counterpart of the meaning-based processes, which typically occur in human cognition. This interpretation emerged from the early developments in quantum cognition , a field that uses quantum mathematics to model human cognitive activity. It benefited from the specific approach taken by the Brussels research group , modelling concepts themselves as quantum entities and minds as measuring apparatus. The article sketches the essential steps of the intellectual journey, going from the first applications of quantum notions and formalisms to human cognition to the proposal of a potentially groundbreaking interpretation of quantum mechanics, offering profound explanations for major quantum phenomena. This was done by drawing numerous parallels with the human conceptual domain and suggesting the existence of a level of cognitive activity that would underlie our physical reality. This means that an increased cross-fertilization between the conceptuality interpretation and quantum cognition is to be expected in the future, both of which are synergistic in furthering our understanding of the nature of reality. This is the first part of a two-part article. In the second part, which can be read independently of the first, the successes of the interpretation will be described in a more systematic way, providing a brief overview of what has been achieved so far. This article is part of the theme issue ‘Quantum theory and topology in models of decision making (Part 1)’.
The emergence of quantum computing has prompted researchers to examine potential parallels between quantum mechanical principles and human cognitive processes. This article explores the theoretical framework of quantum cognition, examining how concepts from quantum mechanics, including superposition, entanglement, and measurement, might inform our understanding of human decision-making, memory, and consciousness. While quantum computing operates on fundamentally different physical principles than biological neural networks, the mathematical formalisms of quantum mechanics offer novel perspectives on cognitive phenomena that classical probability theory struggles to explain. This review critically examines the current state of quantum cognition research, its applications in computational modeling, and the ongoing debates regarding the validity of quantum mechanical analogies in psychological theory. The analysis reveals both promising theoretical insights and significant limitations in applying quantum principles to human cognition, highlighting the need for empirical validation and careful distinction between mathematical analogy and physical reality.
ABSTRACT Recent advances at the intersection of quantum physics, neuroscience, and cognitive science have renewed interest in whether quantum phenomena and quantum‐inspired formalisms can inform models of human cognition and decision‐making. While classical neural and computational models explain many aspects of perception and behavior, they face limitations in accounting for contextuality, order effects, probabilistic reasoning violations, ambiguity resolution, and rapid information integration. This review synthesizes evidence and theoretical frameworks linking quantum‐related principles to cognition, with emphasis on quantum sensing in biological systems, molecular and subcellular quantum‐relevant mechanisms, quantum‐to‐classical transition pathways, quantum‐inspired models of perception and decision‐making, and quantum‐inspired computational approaches. It also extends beyond the probabilistic arm of quantum cognition by considering emerging equilibrium‐based and causal‐logical theories, including mental equilibrium, brain‐universe similarity, mind‐light‐matter unity, quantum emergence, and quantum intelligence. Throughout, the review distinguishes physically instantiated quantum mechanisms from abstract quantum‐like formalisms that model contextuality, mental entanglement, and non‐separable cognitive dynamics without requiring sustained macroscopic quantum coherence in the brain. Finally, it identifies methodological challenges and future directions for advancing quantum cognitive science toward experimentally testable and biologically meaningful theories.
The current chapter explores philosophical and mathematically inspired concepts of quantum cognition paradigm. Quantum cognition is an interdisciplinary domain of overlaps between quantum foundations or quantum information theory concepts and cognitive decision-making processes. The chapter explores frontier works which demonstrate that various quantum-like concepts can describe, explain and even predict human cognitive phenomena better than the standard cognitive science models. Again, no reductionism is implied, or we necessarily do not hold that mind is quantum physical for sure.
The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems. The states of mind or judgment outcomes are highly complex phenomena that happen inside the human body. Decoding these states is significant for improving the quality of technology and providing an impetus to scientific research aimed at understanding the functioning of the human mind. One of the key advantages of quantum wave-functions over conventional classical models is the existence of configurable hidden variables, which provide more data density due to its exponential state-space growth. These hidden variables correspond to the amplitudes of each probable state of the system and allow for the modeling of various intricate aspects of measurable and observable physical quantities. This makes the quantum wave-functions powerful and felicitous to model cognitive states of the human mind, as it inherits the ability to efficiently couple the current context with past experiences temporally and spatially to approach an appropriate future cognitive state. This paper implements and compares some techniques like Variational Quantum Classifiers (VQC), quantum annealing classifiers, and hybrid quantum-classical neural networks, to harness the power of quantum computing for processing cognitive states of the mind by making use of EEG data. It also introduces a novel pipeline by logically combining some of the aforementioned techniques, to predict future cognitive responses. The preliminary results of these approaches are presented and are very encouraging with upto 61.53% validation accuracy.