Entanglement in a quantum neural network based on quantum dots

TL;DR

This paper demonstrates that a quantum neural network built from quantum dots can maintain quantum entanglement and coherence at temperatures as high as 77K, suggesting potential for practical quantum computing applications.

Contribution

It introduces a quantum neural network model based on quantum dots that preserves entanglement at relatively high temperatures, supported by quasiadiabatic path integral simulations.

Findings

Quantum correlations survive at 77K and above.

Entanglement of formation remains significant at high temperatures.

Quantum dot array maintains entangled states under thermal conditions.

Abstract

We studied the quantum correlations between the nodes in a quantum neural network built of an array of quantum dots with dipole-dipole interaction. By means of the quasiadiabatic path integral simulation of the density matrix evolution in a presence of the common phonon bath we have shown the coherence in such system can survive up to the liquid nitrogen temperature of 77K and above. The quantum correlations between quantum dots are studied by means of calculation of the entanglement of formation in a pair of quantum dots with the typical dot size of a few nanometers and the interdot distance of the same order. We have shown that the proposed quantum neural network can keep the mixture of entangled states of QD pairs up to the above mentioned high temperatures.