Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157034
Title: Entanglement of nitrogen-vacancy-center ensembles with initial squeezing
Authors: Pradana, Andri
Chew, Lock Yue
Keywords: Science::Physics
Issue Date: 2021
Source: Pradana, A. & Chew, L. Y. (2021). Entanglement of nitrogen-vacancy-center ensembles with initial squeezing. Physical Review A, 104(2), 022435-. https://dx.doi.org/10.1103/PhysRevA.104.022435
Journal: Physical Review A
Abstract: In this paper, we investigate entanglement of an experimental system of two nitrogen-vacancy-center ensembles which are initially squeezed under the one-axis twisting Hamiltonian. We take into account three scenarios in which initial squeezing and entanglement are mediated by phonons or photons: (a) the phonon-squeezed photon-entangled scenario, (b) the phonon-squeezed phonon-entangled scenario, and (c) the photon-squeezed photon-entangled scenario. For our investigation, we employ the Tavis-Cummings model, which includes dissipative decoherence of the collective spin ensemble, and analyze the system both for a relatively small number of spins and in the limit of a large number of spins using the approach of a quantum master equation. Although evidence in the literature on idealized coupled oscillator systems and coupled quantum kicked tops suggests that initial squeezing can enhance entanglement, we find that, in the realistic system studied in this paper, initial squeezing can improve entanglement overall when the field mode interacts in a particular manner with the two spin ensembles. Our analysis using the Holstein-Primakoff transformation and Wigner characteristic function in the rotating frame of reference shows that the entanglement enhancement is a subtle consequence of the way in which the dissipative decoherence rotates the state of the collective spin ensemble such that enhancement depends on the time-evolved rotated states between the presence and absence of initial squeezing.
URI: https://hdl.handle.net/10356/157034
ISSN: 1050-2947
DOI: 10.1103/PhysRevA.104.022435
Schools: School of Physical and Mathematical Sciences 
Research Centres: Complexity Institute 
Data Science and Artificial Intelligence Research Centre 
Rights: © 2021 American Physical Society. All rights reserved. This paper was published in Physical Review A and is made available with permission of American Physical Society.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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