Natalia E. Kaputkina

Quantum neural networks: Current status and prospects for development

The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

Continuous Wavelet Transform in Quantum Field Theory

We describe the application of the continuous wavelet transform to calculation of the Green functions in quantum field theory: scalar

Entanglement in a quantum neural network based on quantum dots

phi^4

Towards a feasible implementation of quantum neural networks using quantum dots

theory, quantum electrodynamics, quantum chromodynamics. The method of continuous wavelet transform in quantum field theory presented in M.Altaisky Phys. Rev. D81(2010)125003 for the scalar

QUANTUM HIERARCHIC MODELS FOR INFORMATION PROCESSING

phi^4

On wavelet transform in Minkowski space

theory, consists in substitution of the local fields

On the corrections to the Casimir effect depending on the resolution of measurement

phi(x)

Decoherence and Entanglement Simulation in a Model of Quantum Neural Network Based on Quantum Dots

by those dependent on both the position

Indirect excitons in coupled quantum dots and exciton polaritons in optical microcavities in magnetic field

x

Does the Casimir force need corrections

and the resolution