碰撞模型：马尔可夫与非马尔可夫杂质模型

中文摘要 AI 辅助

碰撞模型为研究开放量子系统和引入非马尔可夫性提供了一个灵活的框架。我们提出了一类新颖的碰撞模型，称之为马尔可夫杂质模型，其动机源于信息回流被周期性阻断的物理场景。利用Breuer-Laine-Piilo（BLP）非马尔可夫性度量，我们证明如果p-杂质模型是非马尔可夫的，那么相应的(p+1)-杂质模型也是非马尔可夫的，这意味着存在一个临界p值，在该值处过程从马尔可夫转变为非马尔可夫。我们使用数值模拟来研究这个临界参数如何依赖于系统-辅助量子比特和辅助量子比特-辅助量子比特的相互作用强度。我们发现，尽管存在例外情况，增加任一相互作用强度通常都会降低临界p值，而足够弱的辅助量子比特-辅助量子比特相互作用会导致一个动力学即使在无杂质情况下也保持马尔可夫的区间。最后，我们简要介绍了互补的非马尔可夫杂质模型。

英文摘要

Collision models provide a flexible framework for studying open quantum systems and introducing non-Markovianity. We present a novel class of collision models, which we term Markovian impurity models, motivated by physical scenarios in which information backflow is periodically blocked. Using the Breuer-Laine-Piilo (BLP) measure of non-Markovianity, we show that if a $p$-impurity model is non-Markovian, then the corresponding $(p+1)$-impurity model is also non-Markovian, implying the existence of a critical $p$ at which the process transitions from Markovian to non-Markovian. Numerical simulations are used to investigate how this critical parameter depends on the system-ancilla and ancilla-ancilla interaction strengths. We find that, altough exceptions exist, increasing either interaction strength generally lowers the critical $p$, while sufficiently weak ancilla-ancilla interactions lead to a regime in which the dynamics remain Markovian even in the absence of impurities. Finally, we briefly introduce the complementary non-Markovian impurity model.

发表机构

• The University of Tokyo（东京大学）

机构由 AI 辅助整理，请以论文原文为准。