Che Jiongning, Lu Junjie, Zhang Xiaodong, Dietz Barbara, Chai Guozhi
Lanzhou Center for Theoretical Physics and the Gansu Provincial Key Laboratory of Theoretical Physics, Lanzhou University, Lanzhou University, Lanzhou, Gansu 730000, China.
Institut de Physique de Nice, CNRS UMR 7010, Université Côte d'Azur, 06108 Nice, France.
Phys Rev E. 2021 Apr;103(4-1):042212. doi: 10.1103/PhysRevE.103.042212.
We present experimental and theoretical results for the fluctuation properties in the incomplete spectra of quantum systems with symplectic symmetry and a chaotic dynamics in the classical limit. To obtain theoretical predictions, we extend the random-matrix theory (RMT) approach introduced in Bohigas and Pato [O. Bohigas and M. P. Pato, Phys. Rev. E 74, 036212 (2006)PLEEE81539-375510.1103/PhysRevE.74.036212] for incomplete spectra of quantum systems with orthogonal symmetry. We validate these RMT predictions by randomly extracting a fraction of levels from complete sequences obtained numerically for quantum graphs and experimentally for microwave networks with symplectic symmetry and then apply them to incomplete experimental spectra to demonstrate their applicability. Independently of their symmetry class, quantum graphs exhibit nongeneric features which originate from nonuniversal contributions. Part of the associated eigenfrequencies can be identified in the level dynamics of parameter-dependent quantum graphs and extracted, thereby yielding spectra with systematically missing eigenfrequencies. We demonstrate that, even though the RMT approach relies on the assumption that levels are missing at random, it is possible to determine the fraction of missing levels and assign the appropriate symmetry class by comparison of their fluctuation properties with the RMT predictions.
我们给出了具有辛对称性且在经典极限下具有混沌动力学的量子系统不完全谱中涨落特性的实验和理论结果。为了获得理论预测,我们扩展了Bohigas和Pato [O. Bohigas和M. P. Pato,《物理评论E》74,036212 (2006) PLEEE81539 - 375510.1103/PhysRevE.74.036212] 中引入的用于具有正交对称性的量子系统不完全谱的随机矩阵理论(RMT)方法。我们通过从数值上为量子图以及实验上为具有辛对称性的微波网络获得的完整序列中随机抽取一部分能级来验证这些RMT预测,然后将它们应用于不完全实验谱以证明其适用性。与它们的对称类无关,量子图展现出源于非普适贡献的非一般特征。部分相关的本征频率可以在参数依赖的量子图的能级动力学中识别并提取出来,从而产生具有系统缺失本征频率的谱。我们证明,尽管RMT方法依赖于能级随机缺失的假设,但通过将它们的涨落特性与RMT预测进行比较,仍有可能确定缺失能级的比例并指定适当的对称类。