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1.
Wang Tingting Yin Rongzhang Ye Mingquan Wan Nan Shi Jiadong 《International Journal of Theoretical Physics》2021,60(4):1507-1515
Based on quantum renormalization group (QRG) method, we investigated quantum coherence and quantum phase transition (QPT) in XXZ chain and XY chain, respectively. The results show that both the geometric quantum coherence and entropic coherecne can accurately indicate the QPT at critical point after enough iteration steps. Moreover, the increasing anisotropy parameter destroys the coherence in the XXZ chain, while enhances it in the XY chain. In addition, focused on the XXZ chain we analyzed the nonanalytic phenomena and scaling behaviors with different theoretical exponents in detail.
相似文献2.
Stozhkov Y. I. Filippov M. V. Logachev V. I. Makhmutov V. S. 《Physics of Atomic Nuclei》2021,84(6):1007-1010
Physics of Atomic Nuclei - In the last two decades the new experimental data on cosmic rays concerning energy spectra in a wide energy range up to 10 $${}^{14}$$ eV, isotropy, ratio of positron... 相似文献
3.
M.Y. Pustylnik A.A. Pikalev A.V. Zobnin I.L. Semenov H.M. Thomas O.F. Petrov 《等离子体物理论文集》2021,61(10):e202100126
Low-pressure gas discharge plasmas are known to be strongly affected by the presence of small dust particles. This issue plays a role in the investigations of dust particle-forming plasmas, where the dust-induced instabilities may affect the properties of synthesized dust particles. Also, gas discharges with large amounts of microparticles are used in microgravity experiments, where strongly coupled subsystems of charged microparticles represent particle-resolved models of liquids and solids. In this field, deep understanding of dust–plasma interactions is required to construct the discharge configurations which would be able to model the desired generic condensed matter physics as well as, in the interpretation of experiments, to distinguish the plasma phenomena from the generic condensed matter physics phenomena. In this review, we address only physical aspects of dust–plasma interactions, that is, we always imply constant chemical composition of the plasma as well as constant size of the dust particles. We also restrict the review to two discharge types: dc discharge and capacitively coupled rf discharge. We describe the experimental methods used in the investigations of dust–plasma interactions and show the approaches to numerical modelling of the gas discharge plasmas with large amounts of dust. Starting from the basic physical principles governing the dust–plasma interactions, we discuss the state-of-the-art understanding of such complicated, discharge-type-specific phenomena as dust-induced stratification and transverse instability in a dc discharge or void formation and heartbeat instability in an rf discharge. 相似文献
4.
In this work we extend the method of the constrained large-eddy simulation(CLES) to simulate the turbulent flow over inhomogeneous rough walls. In the original concept of CLES, the subgrid-scale(SGS) stress is constrained so that the mean part and the fluctuation part of the SGS stress can be modelled separately to improve the accuracy of the simulation result. Here in the simulation of the rough-wall flows, we propose to interpret the extra stress terms in the CLES formulation as the roughness-induced stress so that the roughness inhomogeneity can be incorporated by modifying the formulation of the constrained SGS stress. This is examined with the simulations of the channel flow with the spanwise alternating high/low roughness strips. Then the CLES method is employed to investigate the temporal response of the turbulence to the change of the wall condition from rough to smooth. We demonstrate that the temporal development of the internal boundary layer is just similar to that in a spatial rough-tosmooth transition process, and the spanwise roughness inhomogeneity has little impact on the transition process. 相似文献
5.
Kobayashi M. Zhang Y. Ishikawa H. Sun J. Oddershede J. Juul Jensen D. Miura H. 《Experimental Mechanics》2021,61(5):817-828
Experimental Mechanics - The internal strain distribution developing during plastic deformation is important for understanding the mechanical properties of polycrystalline materials. Such... 相似文献
6.
Physics of Atomic Nuclei - We have investigated the robustness of the spin-navigator based method for manipulating the beam polarization to bend magnet installation errors. Toward that end,... 相似文献
7.
Lebedev D. V. Egorov V. V. Shvetsov A. V. Zabrodskaya Y. A. Isaev-Ivanov V. V. Konevega A. L. 《Crystallography Reports》2021,66(2):242-253
Crystallography Reports - The review describes the application of small-angle scattering (SAS) of neutrons and complementary methods to study the structures of biomacromolecules. Here we cover SAS... 相似文献
8.
The Coronavirus disease 2019 (COVID-19) has become one of the threats to the world. Computed tomography (CT) is an informative tool for the diagnosis of COVID-19 patients. Many deep learning approaches on CT images have been proposed and brought promising performance. However, due to the high complexity and non-transparency of deep models, the explanation of the diagnosis process is challenging, making it hard to evaluate whether such approaches are reliable. In this paper, we propose a visual interpretation architecture for the explanation of the deep learning models and apply the architecture in COVID-19 diagnosis. Our architecture designs a comprehensive interpretation about the deep model from different perspectives, including the training trends, diagnostic performance, learned features, feature extractors, the hidden layers, the support regions for diagnostic decision, and etc. With the interpretation architecture, researchers can make a comparison and explanation about the classification performance, gain insight into what the deep model learned from images, and obtain the supports for diagnostic decisions. Our deep model achieves the diagnostic result of 94.75%, 93.22%, 96.69%, 97.27%, and 91.88% in the criteria of accuracy, sensitivity, specificity, positive predictive value, and negative predictive value, which are 8.30%, 4.32%, 13.33%, 10.25%, and 6.19% higher than that of the compared traditional methods. The visualized features in 2-D and 3-D spaces provide the reasons for the superiority of our deep model. Our interpretation architecture would allow researchers to understand more about how and why deep models work, and can be used as interpretation solutions for any deep learning models based on convolutional neural network. It can also help deep learning methods to take a step forward in the clinical COVID-19 diagnosis field. 相似文献
9.
Russian Physics Journal - Connection of Pauli’s principle with the nontrivial structure of the fermion supertime is shown. When supersymmetry is localized as supergravitation, fields of... 相似文献