量子芝诺-反芝诺效应与宇称-时间对称破缺跃迁的统一
Unification of quantum Zeno-anti Zeno effects and parity-time symmetry breaking transitions
AI总结：
本文提出将耗散哈密顿量映射到PT对称非厄米哈密顿量的通用框架，统一量子芝诺-反芝诺效应与PT对称破缺跃迁，并揭示两能级系统中QZE/QAZE与PTS/PTB相之间的对应关系。
摘要：
任何不稳定量子态的衰变都可以通过精心设计的测量来抑制或增强，这分别被称为量子芝诺效应（QZE）或反芝诺效应（QAZE）。迄今为止，关于QZE（QAZE）跃迁的研究已经扩展到各种系统-环境耦合，其中时间演化不仅可以通过投影测量被抑制（增强），还可以通过耗散过程被抑制（增强）。然而，目前仍缺乏一个能够推广到任意耗散强度和周期性的通用判据。在本文中，我们展示了一个统一QZE-QAZE效应与宇称-时间（PT）对称破缺跃迁的通用框架，其中与测量效应相关的耗散哈密顿量被映射到一个PT对称的非厄米哈密顿量上，从而利用PT对称跃迁来区分QZE（QAZE）及其交叉行为。作为一个具体例子，我们表明，在一个周期性耦合到耗散环境的两能级系统中，QZE起始于一个例外点（EP），该点将PT对称（PTS）相与PT对称破缺（PTB）相分开，并终止于最大PT对称破缺的共振点（RP）；而QAZE则延伸至PTB相的其余部分，并保持整个PTS相。这些发现揭示了非厄米量子动力学中QZE-QAZE与PTS-PTB相之间的隐藏关系。
英文摘要：
The decay of any unstable quantum state can be inhibited or enhanced by carefully tailored measurements, known as the quantum Zeno effect (QZE) or anti-Zeno effect (QAZE). To date, studies of QZE (QAZE) transitions have since expanded to various system-environment coupling, in which the time evolution can be suppressed (enhanced) not only by projective measurement but also through dissipation processes. However, a general criterion, which could extend to arbitrary dissipation strength and periodicity, is still lacking. In this letter, we show a general framework to unify QZE-QAZE effects and parity-time (PT) symmetry breaking transitions, in which the dissipative Hamiltonian associated to the measurement effect is mapped onto a PT-symmetric non- Hermitian Hamiltonian, thus applying the PT symmetry transitions to distinguish QZE (QAZE) and their crossover behavior. As a concrete example, we show that, in a two-level system periodically coupled to a dissipative environment, QZE starts at an exceptional point (EP), which separates the PT-symmetric (PTS) phase and PT-symmetry broken (PTB) phase, and ends at the resonance point (RP) of the maximum PT-symmetry breaking; while QAZE extends the rest of PTB phase and remains the whole PTS phase. Such findings reveal a hidden relation between QZE-QAZE and PTS-PTB phases in non-Hermitian quantum dynamics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
