Comment on "Time-Dependent Density-Matrix Renormalization Group: A Systematic Method for the Study of Quantum Many-Body Out-of- Equilibrium Systems"

In a recent Letter [Phys. Rev. Lett. 88, 256403(2002), cond-mat/0109158] Cazalilla and Marston proposed a time-dependent density- matrix renormalization group (TdDMRG) algorithm for the accurate evaluation of out-of-equilibrium properties of quantum many-body systems. For a point contact junction between two Luttinger liquids, a current oscillation develops after initial transient in the insulating regime. Here we would like to point out that (a) the observed oscillation is an artifact of the method; (b) the TdDMRG can be significantly improved by incorporating the non-equilibrium evolution of the goundstate into the density matrix.Comment: 1 page, 2 figure

Shock Diffraction by Convex Cornered Wedges for the Nonlinear Wave System

We are concerned with rigorous mathematical analysis of shock diffraction by two-dimensional convex cornered wedges in compressible fluid flow governed by the nonlinear wave system. This shock diffraction problem can be formulated as a boundary value problem for second-order nonlinear partial differential equations of mixed elliptic-hyperbolic type in an unbounded domain. It can be further reformulated as a free boundary problem for nonlinear degenerate elliptic equations of second order. We establish a first global theory of existence and regularity for this shock diffraction problem. In particular, we establish that the optimal regularity for the solution is $C^{0,1}$ across the degenerate sonic boundary. To achieve this, we develop several mathematical ideas and techniques, which are also useful for other related problems involving similar analytical difficulties.Comment: 50 pages;7 figure

Reply to "Comment on 'Fano resonance for Anderson Impurity Systems' "

In a recent Comment, Kolf et al. (cond-mat/0503669) state that our analysis of the Fano resonance for Anderson impurity systems [Luo et al., Phys. Rev. Lett 92, 256602 (2004)] is incorrect. Here we want to point out that their comments are not based on firm physical results and their criticisms are unjustified and invalid.Comment: 1 page, 1 figure, to appear in PR

Plaquette order and deconfined quantum critical point in the spin-1 bilinear-biquadratic Heisenberg model on the honeycomb lattice

We have precisely determined the ground state phase diagram of the quantum spin-1 bilinear-biquadratic Heisenberg model on the honeycomb lattice using the tensor renormalization group method. We find that the ferromagnetic, ferroquadrupolar, and a large part of the antiferromagnetic phases are stable against quantum fluctuations. However, around the phase where the ground state is antiferroquadrupolar ordered in the classical limit, quantum fluctuations suppress completely all magnetic orders, leading to a plaquette order phase which breaks the lattice symmetry but preserves the spin SU(2) symmetry. On the evidence of our numerical results, the quantum phase transition between the antiferromagnetic phase and the plaquette phase is found to be either a direct second order or a very weak first order transition.Comment: 6 pages, 9 figures, published versio

Renormalization of tensor-network states

We have discussed the tensor-network representation of classical statistical or interacting quantum lattice models, and given a comprehensive introduction to the numerical methods we recently proposed for studying the tensor-network states/models in two dimensions. A second renormalization scheme is introduced to take into account the environment contribution in the calculation of the partition function of classical tensor network models or the expectation values of quantum tensor network states. It improves significantly the accuracy of the coarse grained tensor renormalization group method. In the study of the quantum tensor-network states, we point out that the renormalization effect of the environment can be efficiently and accurately described by the bond vector. This, combined with the imaginary time evolution of the wavefunction, provides an accurate projection method to determine the tensor-network wavfunction. It reduces significantly the truncation error and enable a tensor-network state with a large bond dimension, which is difficult to be accessed by other methods, to be accurately determined.Comment: 18 pages 23 figures, minor changes, references adde

Thermodynamic properties of tetrameric bond-alternating spin chains

Thermodynamic properties of a tetrameric bond-alternating Heisenberg spin chain with ferromagnetic-ferromagnetic-antiferromagnetic-antiferromagnetic exchange interactions are studied using the transfer-matrix renormalization group and compared to experimental measurements. The temperature dependence of the uniform susceptibility exhibits typical ferrimagnetic features. Both the uniform and staggered magnetic susceptibilities diverge in the limit $T\to 0$, indicating that the ground state has both ferromagnetic and antiferromagnetic long-range orders. A double-peak structure appears in the temperature dependence of the specific heat. Our numerical calculation gives a good account for the temperature and field dependence of the susceptibility, the magnetization, and the specific heat for Cu(3-Clpy)$_{2}$(N$_{3}$)$_{2}$ (3-Clpy=3-Chloroyridine).Comment: 8 pages, 12 figures; Replaced with final version accepted in Phys. Rev.

Electron quantum interference in epitaxial antiferromagnetic NiO thin films

The electron reflectivity from NiO thin films grown on Ag(001) has been systematically studied as a function of film thickness and electron energy. A strong electron quantum interference effect was observed from the NiO film, which is used to derive the unoccupied band dispersion above the Fermi surface along the Γ-X direction using the phase accumulation model. The experimental bands agree well with first-principles calculations. A weaker electron quantum interference effect was also observed from the CoO film

TUMK-ELM: A fast unsupervised heterogeneous data learning approach

© 2013 IEEE. Advanced unsupervised learning techniques are an emerging challenge in the big data era due to the increasing requirements of extracting knowledge from a large amount of unlabeled heterogeneous data. Recently, many efforts of unsupervised learning have been done to effectively capture information from heterogeneous data. However, most of them are with huge time consumption, which obstructs their further application in the big data analytics scenarios, where an enormous amount of heterogeneous data are provided but real-time learning are strongly demanded. In this paper, we address this problem by proposing a fast unsupervised heterogeneous data learning algorithm, namely two-stage unsupervised multiple kernel extreme learning machine (TUMK-ELM). TUMK-ELM alternatively extracts information from multiple sources and learns the heterogeneous data representation with closed-form solutions, which enables its extremely fast speed. As justified by theoretical evidence, TUMK-ELM has low computational complexity at each stage, and the iteration of its two stages can be converged within finite steps. As experimentally demonstrated on 13 real-life data sets, TUMK-ELM gains a large efficiency improvement compared with three state-of-the-art unsupervised heterogeneous data learning methods (up to 140 000 times) while it achieves a comparable performance in terms of effectiveness

Parent-adolescent attachment and peer attachment associated with Internet Gaming Disorder: a longitudinal study of first-year undergraduate students

Background and aims: Given that Internet Gaming Disorder (IGD) has tentatively been included in DSM-5 as a psychiatric disorder, it is important that the effect of parental and peer attachment in the development of IGD is further explored. Methods: Utilizing a longitudinal design, this study investigated the bidirectional association between perceived Q1 parent-adolescent attachment, peer attachment, and IGD among 1,054 first-year undergraduate students (58.8% female). The students provided demographic information (e.g., age, gender) and were assessed using the nine-item Internet Gaming Disorder Scale and the Inventory of Parent and Peer Attachment. Assessments occurred three times, six months apart (October 2017; April 2018; October 2018). Results: Cross-lagged panel models suggested that IGD weakly predicted subsequent mother attachment but significantly negatively predicted father attachment. However, father and mother attachment could not predict subsequent IGD. Moreover, peer attachment has bidirectional association with IGD. Further, the model also demonstrated stable crosssectional negative correlations between attachment and IGD across all three assessments. Discussion and conclusions: The findings of the present study did not show a bidirectional association between parental attachment and IGD, but they did show a negative bidirectional association between peer attachment and IGD. The results suggested previous cross-sectional associations between IGD and attachment, with larger links among males than females at the first measurement point. We found that peer attachment could negatively predict subsequent IGD, which indicates that peer attachment plays an important role in preventing addictive gaming behaviors for university students