Graphene lattice-layer entanglement under non-Markovian phase noise

TL;DR

This paper investigates how non-Markovian phase noise affects the entanglement dynamics of lattice-layer states in bilayer graphene, revealing entanglement decay, revivals, and the influence of memory effects in noisy environments.

Contribution

It models non-Markovian noise effects on bilayer graphene's lattice-layer entanglement, linking noiseless dynamics to stochastic noise processes and analyzing entanglement dissipation and revival patterns.

Findings

Entanglement exhibits revivals and decay depending on initial states.

Memory effects can partially counteract noise-induced decoherence.

Non-Markovian noise models like Ornstein-Uhlenbeck are effective in this context.

Abstract

The evolution of single particle excitations of bilayer graphene under effects of non-Markovian noise is described with focus on the decoherence process of lattice-layer (LL) maximally entangled states. Once that the noiseless dynamics of an arbitrary initial state is identified by the correspondence between the tight-binding Hamiltonian for the AB-stacked bilayer graphene and the Dirac equation -- which includes pseudovector- and tensor-like field interactions -- the noisy environment is described as random fluctuations on bias voltage and mass terms. The inclusion of noisy dynamics reproduces the Ornstein-Uhlenbeck processes: a non-Markovian noise model with a well-defined Markovian limit. Considering that an initial amount of entanglement shall be dissipated by the noise, two profiles of dissipation are identified. On one hand, for eigenstates of the noiseless Hamiltonian, deaths and revivals of entanglement are identified along the oscillation pattern for long interaction periods. On the other hand, for departing LL Werner and Cat states, the entanglement is suppressed although, for both cases, some identified memory effects compete with the pure noise-induced decoherence in order to preserve the the overall profile of a given initial state.