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.
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.
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.
Abstract Quantum logics are non-classical logics defined from the mathematical formalism of quantum mechanics. While they are conventionally used to model inferential processes in physics, their scope of application is potentially much broader. We argue that quantum logics can serve as a framework to model human cognition, as their semantics seem able to capture not only how people make inferences about quantum mechanics, but also how they reason in general. We begin by defining quantum logics from an algebraic perspective in a classical first-order setting. Next, we present findings from cognitive science that suggest these logics are apt to characterize human reasoning. We then consider how such a connection between quantum logics and cognition contributes to longstanding philosophical debates about the epistemological status of logic and the problem of adoption. Finally, we discuss how cognitive applications of quantum logics could advance our understanding of human psychology and even quantum foundations.
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.
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.
We extend an empirically grounded theory of the existence of quantum computer. The main question that we are considering is a question about the quantum computer’s possibility of existence and creation. As empirical evidence, we use logic, which we show in cognitive perspective. For a definition of the computer, we use a formal definition of Turing machine. By formulating many definitions abstractly and phenomenologically we go around the areas of quantum physics, quantum computing and other quantum-related fields of science which could give an unambiguous answer to our question about the essence of quantum computer and which is developed so they can’t. In many ways, it makes this theory about the existence of quantum computer universal for these areas, although less applied for them. We consider some corollary of the essences of quantum computer, including the possibility of quantum computer for the human. References to research of cognitive nature of logic suggest empirical basis which we follow in our theory.
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.