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Marina V Bastrakova1, Dmitrii S Pashin1, Dmitriy A Rybin1

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We studied adiabatic neural cells in a quantum regime for hybrid classical-quantum networks. Results show conditions for achieving the neuron

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Area of Science:

  • Quantum computing
  • Artificial intelligence
  • Computational neuroscience

Background:

  • Hybrid classical-quantum systems offer novel computational paradigms.
  • Artificial neural networks are foundational to machine learning.
  • Quantum dynamics can influence classical system behavior.

Purpose of the Study:

  • To investigate the quantum dynamics of an adiabatic neural cell within a perceptron artificial neural network.
  • To analyze a hybrid system where a quantum co-processor adjusts a classical neural network's configuration.
  • To determine the conditions for achieving a sigmoid activation function in such a quantum-classical hybrid neuron.

Main Methods:

  • Analytical and numerical studies were employed.
  • The research considered non-adiabatic processes and dissipation effects.
  • Quantum coherent oscillations were analyzed for their smoothing due to these factors.

Main Results:

  • The study identified specific conditions under which the neural cell exhibits the desired sigmoid activation function.
  • Non-adiabatic processes and dissipation were shown to smooth quantum coherent oscillations.
  • The dynamics of adiabatic neural cells in a quantum regime were characterized.

Conclusions:

  • The findings provide insights into the behavior of hybrid quantum-classical neural networks.
  • Achieving a functional sigmoid activation in a quantum-assisted neuron is feasible under certain conditions.
  • This research contributes to the development of quantum-enhanced artificial intelligence.