Decoherence in a quantum neural network

TL;DR

This paper investigates the coherence dynamics of a quantum neural network modeled by a spin-star system, analyzing how different spin couplings affect quantum coherence in a dissipative environment.

Contribution

It introduces a spin-star model to study quantum coherence in neural networks and evaluates the impact of various spin couplings on coherence time in a Markov environment.

Findings

Ising-type coupling reduces coherence time rapidly

Central spin coherence can be prolonged under specific parameters

Quantum coherence is a key resource for quantum neural networks

Abstract

In this study, we propose a spin-star model for spin-(1/2) particles in order to examine the coherence dynamics of a quantum neural network (QNN) unit. Since quantum computing paradigm promises advantages over their classical counterparts, quantum versions of neural networks can be examined in this context. We focus on quantum coherence as a natural resource for quantum computing and investigate the central spin coherence of a spin star model in the time domain in a dissipative environment. More particularly, we investigate the extend to which the central spin coherence time would be prolonged under specific parameters and spin-coupling Hamiltonians in a Markov environment. We show that Ising-type spin coupling is not desirable since it rapidly diminishes the coherence time in a dissipative environment.