Machine learning studies for the effects of probes and cavity on quantum synchronization
Author:
Meng Qing-Yu1, Hu Yong1, Yang Qing1, Zhu Qin-Sheng1, Li Xiao-Yu2
Affiliation:
1. School of Physics, University of Electronic Science and Technology of China , Chengdu , 610054 , China 2. School of Information and Software Engineering, University of Electronic Science and Technology of China , Chengdu , 610054 , China
Abstract
Abstract
As an important technology of the quantum detection, the quantum synchronization detection is always used in the detection or measurement of some quantum systems. A probing model is established to describe the probing of a qubit system in the cavity field and to reveal the effect of the environment (cavity) on the quantum synchronization occurrence, as well as the interactions among environment, a qubit system, and probing equipment. By adjusting the frequency of the probe, the in-phase, anti-phase, and out-of-phase synchronization can be achieved. Simultaneously, the effect of
γ
3
${\gamma }_{3}$
which describes the interaction strength between the probe and environments for quantum synchronization is discussed under different Ohmic dissipation index
s
. Finally, the machine learning method is applied to present an optimization for classification and regression of synchronization transition dependent on
s
and
γ
3
${\gamma }_{3}$
.
Publisher
Walter de Gruyter GmbH
Subject
Physical and Theoretical Chemistry,General Physics and Astronomy,Mathematical Physics
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