Steady-state coherence of spin-boson model in a general non-Markovian environment

IF 1.5 4区 物理与天体物理 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Fangqin Jin, Wen-Long You, Yue Dai, Tian-Cheng Yi, Yuli Dong, Chengjie Zhang
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引用次数: 0

Abstract

Based on the quantum coherence theory, we employ the [Formula: see text]-norm measure to explore the steady-state coherence (SSC) in the spin-boson model. In this model, the environment is a non-Markovian bosonic bath with Ohmic-like spectral density. More generally, the interaction coupling between the qubit and the environment is a linear superposition of pure dephasing and pure damping coupling. Governed by the non-Markovian dynamics, some compact expressions of the SSC have been obtained at both zero temperature and high temperature. It shows that the hybrid coupling significantly affects the SSC. Moreover, a comprehensive analysis has been conducted to investigate the effects of various crucial factors, including the temperature of the bosonic bath, the qubit’s tunneling and the Ohmicity parameter. This analysis provides an effective approach for maintaining a relatively high SSC by manipulating system parameters.
一般非马尔可夫环境下自旋玻色子模型的稳态相干性
基于量子相干理论,我们采用[公式:见文]范数测度来探讨自旋玻色子模型中的稳态相干性(SSC)。在这个模型中,环境是一个具有类欧姆谱密度的非马尔可夫玻色子浴。更一般地说,量子比特与环境之间的相互作用耦合是纯减相和纯阻尼耦合的线性叠加。在非马尔可夫动力学的约束下,得到了SSC在零温度和高温下的一些紧致表达式。结果表明,杂化耦合对SSC有显著影响。此外,还对玻色子槽的温度、量子比特的隧穿和欧姆度参数等关键因素的影响进行了综合分析。这种分析提供了一种通过操纵系统参数来维持相对较高SSC的有效方法。
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来源期刊
International Journal of Modern Physics C
International Journal of Modern Physics C 物理-计算机:跨学科应用
CiteScore
3.00
自引率
15.80%
发文量
158
审稿时长
4 months
期刊介绍: International Journal of Modern Physics C (IJMPC) is a journal dedicated to Computational Physics and aims at publishing both review and research articles on the use of computers to advance knowledge in physical sciences and the use of physical analogies in computation. Topics covered include: algorithms; computational biophysics; computational fluid dynamics; statistical physics; complex systems; computer and information science; condensed matter physics, materials science; socio- and econophysics; data analysis and computation in experimental physics; environmental physics; traffic modelling; physical computation including neural nets, cellular automata and genetic algorithms.
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