Entropic uncertainty relations in the spin-1 Heisenberg model
Entropic uncertainty relations in the spin-1 Heisenberg model
复制标题
spin-1 海森堡模型中的熵不确定性关系
DOI:
10.1007/s11128-019-2196-7
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发表时间:
2019-01
影响因子:
2.5
通讯作者:
Ye Liu
中科院分区:
文献类型:
--
作者:
Shi Wei Nan;Ming Fei;Wang Dong;Ye Liu
The uncertainty relations build an intrinsic lower bound to the measurement precision for arbitrary two incompatible observables and hence deemed as a backbone in quantum theory, strikingly distinguishing from classical physics. In this work, we examine the quantum-memory-assisted entropic uncertainty relations (QMA-EUR) in two-qutrit spin-1 Heisenberg XYZ and XXX chains under homogeneous magnetic fields, respectively. We specifically derive the dynamical evolution of QMA-EUR for various incompatible measurements on Pauli operators (mutually unbiased bases) and SU(3) generators in the Heisenberg XXX and XYZ models when spinAis the object to be measured andBis served as quantum memory during information processing. Notably, it has been found in the case of mutual unbiased-base measurements that, firstly, the larger coupling strengthJbetweenAandBcan induce the degradation of the measurement’s uncertainty; secondly, the entropic uncertainty is extremely dependent on the coupling strength and the external magnetic field, which would bring the uncertainty on the inflation. In addition, we unveil the dynamical behaviors of the uncertainty measured on SU(3) generators, and it proves that the uncertainty’s dynamics are subtly different from those in the former. Moreover, we explore the relationship between the entropic uncertainty and the system’s entanglement (negativity) and declare that the dynamics of the entropic uncertainty of interest are approximately anti-correlated with that of negativity. At last, the entanglement’s dynamics of the probed system in the XXX and XYZ models are revealed and analyzed by means of negativity, respectively. Hence, our observations might pave the way to understand the dynamical traits of the entropic uncertainty during measurement-based information processing.
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