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Journal of Optical Technology

Holographic implementation of quantum-like cognitive models

Alexander V. Pavlov

Published Jun 1, 2025• 0 citations
Publisher

Abstract

Subject of study. A 4 f Fourier-holography scheme with phase conjugation in the correlation plane and the corresponding Grossberg “Instar” neural-network model were examined to assess the feasibility of implementing quantum-like models of information processing. Aim of study. The aim was to develop a Fourier-holography scheme model consistent with the mathematical formalism of quantum mechanics used in quantum-like cognitive models. Method. Analytical modeling and numerical simulations were performed by representing the processed information with a homogeneous isotropic random field model. Main results. The results showed that the Fourier-holography setup incorporating nonlinear phase conjugation in the correlation plane could serve as a limited analog of a quantum system in terms of parallel processing and choice from a superposition. In this case, the choice was not random; rather, it was determined by the nonlinear transfer function of the phase-conjugating mirror. The shift-invariance, ensured by a thin Fourier hologram, imparted an additional capability—making decisions in the form of a superposition described by a linear prediction model; some researchers consider this approach as a possible mechanism underlying the phenomenon of intuition. Practical significance. An analytical description, consistent with the information-processing model, is required for developing holographic simulators of quantum information-processing systems and computing devices.

DOI
10.1364/jot.92.000347

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Subject of study. A 4 f Fourier-holography scheme with phase conjugation in the correlation plane and the corresponding Grossberg “Instar” neural-network model were examined to assess the feasibility of implementing quantum-like models of information processing. Aim of study. The aim was to develop a Fourier-holography scheme model consistent with the mathematical formalism of quantum mechanics used in quantum-like cognitive models. Method. Analytical modeling and numerical simulations were performed by representing the processed information with a homogeneous isotropic random field model. Main results. The results showed that the Fourier-holography setup incorporating nonlinear phase conjugation in the correlation plane could serve as a limited analog of a quantum system in terms of parallel processing and choice from a superposition. In this case, the choice was not random; rather, it was determined by the nonlinear transfer function of the phase-conjugating mirror. The shift-invariance, ensured by a thin Fourier hologram, imparted an additional capability—making decisions in the form of a superposition described by a linear prediction model; some researchers consider this approach as a possible mechanism underlying the phenomenon of intuition. Practical significance. An analytical description, consistent with the information-processing model, is required for developing holographic simulators of quantum information-processing systems and computing devices.
The article is dedicated to the search for a biologically motivated mechanism of the cognitive phenomenon of violation of the classical formula of total probability for the disjunction of incompatible events, which is considered by a number of researchers as a quantum-like phenomenon. A classical mechanism implemented by the 6f Fourier holography scheme of the resonant architecture that does not require reference to quantum mechanics either in its physical nature or at the level of formalism is demonstrated. In the analysis, the decision-making is interpreted as a choice of alternatives by using the non-cooperative game "Prisoner's Dilemma". The approach to the task is based on the search for a mechanism for forming a conditional estimate under a condition that contradicts the rule of monotonous decision logic. It is demonstrated that this estimate, in contrast to the unconditional and conditional one with a non-contradictory condition, is formed by logic with exception. The ring architecture of the holographic setup corresponds to the biologically inspired neural network concept of the excitation ring and implements cognitive dissonance on logic with exception. Conditions and ranges of violation of the classical formula of total probability in relation to the correlation radius of the reference image recorded in a hologram storing the monotone logic inference rule are analytically determined. The analytical model is confirmed by a quantitative coincidence of the results of numerical modeling with the published results of natural experiments.
A Fourier-holography scheme with superimposed holograms and phase conjugation is considered. It is shown that the sub-holograms, arising from the recording of superimposed holograms due to quadratic nonlinearity of the exposure characteristics of holographic recording media, form the connections necessary for the realisation of the quantum-logic mechanism of sequential projection of the input vector onto the subspaces of the recorded images. A classical mechanism of the 'Linda' cognitive phenomenon belonging to the category of quantum-like ones is described. An experimental illustration of the self-sustained formation of sub-holograms due to the nonlinearity of the exposure characteristics of holographic recording media is given.
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.
We present the quantum-like model of information processing by the brain’s neural networks. The model does not refer to genuine quantum processes in the brain. In this model, uncertainty generated by the action potential of a neuron is represented as quantum-like superposition of the basic mental states corresponding to a neural code. Neuron’s state space is described as complex Hilbert space (quantum information representation). The brain’s psychological functions perform self-measurements by extracting concrete answers to questions (solutions of problems) from quantum information states. This extraction is modeled in the framework of open quantum systems theory. In this way, it is possible to proceed without appealing to the state’s collapse. Dynamics of the state of psychological function F is described by the quantum master equation. Its stationary states represent classical statistical mixtures of possible outputs of F (decisions). This model can be used for justification of quantum-like modeling cognition and decision-making. The latter is supported by plenty of statistical data collected in cognitive psychology.
: the interpretation of phases in quantum-like state superpositions. In QLM, system states are represented by normalized vectors in a complex Hilbert space, |ψ⟩=∑kXk|k⟩, where the squared amplitudes Pk=|Xk|2 are outcome probabilities. However, the meaning of the phase factors eiϕk in the coefficients Xk=Pkeiϕk has remained elusive, often treating them as purely phenomenological parameters. This practice, while successful in describing cognitive interference effects (the "interference of the mind"), has drawn criticism for expanding the model's parameter space without a clear physical or cognitive underpinning. Building on a recent framework that connects QCDM to neuronal network activity, we propose a concrete interpretation. We argue that the phases in quantum-like superpositions correspond directly to the phases of random oscillations generated by neuronal circuits in the brain. This interpretation not only provides a natural, non-phenomenological basis for phase parameters within QCDM but also helps to bridge the gap between quantum-like models and classical neurocognitive frameworks, offering a consistent physical analogy for the descriptive power of QLM.