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The Mott insulator is the quintessential strongly correlated electronic state. We obtain complete insight into the physics of the two-dimensional Mott insulator by extending the slave-fermion (holon-doublon) description to finite temperatures. We first benchmark its predictions against state-of-the-art quantum Monte Carlo simulations, demonstrating quantitative agreement. Qualitatively, the short-ranged spin fluctuations both induce holon-doublon bound states and renormalize the charge sector to form the Hubbard bands. The Mott gap is understood as the charge gap renormalized downwards by these spin fluctuations. As temperature increases, the Mott gap closes before the charge gap, causing a pseudogap regime to appear naturally during the melting of the Mott insulator., 12 pages, 10 figures

The Chebyshev expansion offers a numerically efficient and easy-implement algorithm for evaluating dynamic correlation functions using matrix product states (MPS). In this approach, each recursively generated Chebyshev vector is approximately represented by an MPS. However, the recurrence relations of Chebyshev polynomials are broken by the approximation, leading to an error which is accumulated with the increase of the order of expansion. Here we propose a reorthonormalization approach to remove this error introduced in the loss of orthogonality of the Chebyshev polynomials. Our approach, as illustrated by comparison with the exact results for the one-dimensional XY and Heisenberg models, improves significantly the accuracy in the calculation of dynamical correlation functions., 9 pages, 8 figures

In the tensor-network framework, the expectation values of two-dimensional quantum states are evaluated by contracting a double-layer tensor network constructed from initial and final tensor-network states. The computational cost of carrying out this contraction is generally very high, which limits the largest bond dimension of tensor-network states that can be accurately studied to a relatively small value. We propose an optimized contraction scheme to solve this problem by mapping the double-layer tensor network onto an intersected single-layer tensor network. This reduces greatly the bond dimensions of local tensors to be contracted and improves dramatically the efficiency and accuracy of the evaluation of expectation values of tensor-network states. It almost doubles the largest bond dimension of tensor-network states whose physical properties can be efficiently and reliably calculated, and it extends significantly the application scope of tensor-network methods., 7 pages, 6 figures, accepted version for Phys. Rev. B. The title is changed for easier understanding

Among hundreds of spinel oxides, $\mathrm{LiT}{\mathrm{i}}_{2}{\mathrm{O}}_{4}$ (LTO) is the only one that exhibits superconductivity (${T}_{\mathrm{c}}\ensuremath{\sim}13\phantom{\rule{0.16em}{0ex}}\mathrm{K}$). Although the general electron-phonon coupling is still the main mechanism for electron pairing in LTO, unconventional behaviors such as the anomalous magnetoresistance, anisotropic orbital/spin susceptibilities, etc. reveal that both the spin and the orbital interactions should also be considered for understanding the superconductivity. Here we investigate tunneling spectra of [111]-, [110]-, and [001]-oriented high quality LTO thin films. Several bosonic modes in tunneling spectra are observed in the [111]- and [110]-oriented films but not in [001]-oriented ones, and these modes still exist at $T=2{T}_{\mathrm{c}}$ and beyond the upper critical field, which are confirmed as stemming from electron-phonon interaction by DFT calculations. These modes only appear in special surface orientations, indicating that the electron-phonon coupling in LTO system is highly anisotropic and may be enhanced by an orbital-related state. The anisotropic electron-phonon coupling should be taken seriously in understanding the nature of LTO superconductivity.

The restricted Boltzmann machine (RBM) is one of the fundamental building blocks of deep learning. RBM finds wide applications in dimensional reduction, feature extraction, and recommender systems via modeling the probability distributions of a variety of input data including natural images, speech signals, and customer ratings, etc. We build a bridge between RBM and tensor network states (TNS) widely used in quantum many-body physics research. We devise efficient algorithms to translate an RBM into the commonly used TNS. Conversely, we give sufficient and necessary conditions to determine whether a TNS can be transformed into an RBM of given architectures. Revealing these general and constructive connections can cross-fertilize both deep learning and quantum many-body physics. Notably, by exploiting the entanglement entropy bound of TNS, we can rigorously quantify the expressive power of RBM on complex data sets. Insights into TNS and its entanglement capacity can guide the design of more powerful deep learning architectures. On the other hand, RBM can represent quantum many-body states with fewer parameters compared to TNS, which may allow more efficient classical simulations., Comment: 18 pages, 12 figures + 2 appendices; Code implementations at https://github.com/yzcj105/rbm2mps

We investigate the critical behavior and the duality property of the ferromagnetic $q$-state clock model on the square lattice based on the tensor-network formalism. From the entanglement spectra of local tensors defined in the original and dual lattices, we obtain the exact self-dual points for the model with $q \leq 5 $ and approximate self-dual points for $q \geq 6$. We calculate accurately the lower and upper critical temperatures for the six-state clock model from the fixed-point tensors determined using the higher-order tensor renormalization group method and compare with other numerical results., Comment: 5 pages, 4 figures

This paper investigates the common causes of coal mine belt conveyor accidents, including splice breakage, longitudinal rip, deviation, etc. Then, main real time monitoring methods and techniques for these coal mine belt conveyor accidents are classified and their problems are analyzed and summarized. At last, an intelligent real time monitoring system for coal mine conveyor belt which is under development is presented.

Frustrated quantum magnetism has moved to the forefront of physics research, posing fundamental questions concerning quantum disordered states, entanglement, topology and the nature of the quantum wavefunction. The defining problem in the field is one of the simplest, the ground state of the nearest-neighbour $S = 1/2$ antiferromagnetic Heisenberg model on the kagome lattice, but has defied all theoretical and numerical methods employed to date. We apply the formalism of tensor-network states (TNS), specifically the method of projected entangled simplex states (PESS), whose combination of a correct accounting for multipartite entanglement and infinite system size provides qualitatively new insight. By studying the ground-state energy, the staggered magnetization we find at all finite tensor bond dimensions and the effects of a second-neighbour coupling, we demonstrate that the ground state is a gapless spin liquid. We discuss the comparison with other numerical studies and the physical interpretation of the gapless ground state., Comment: 8 pages, 4 figures, revised version accepted for publication in PRL

As a gear device driving fire pump, fire ladder, rescue truck crane and other fire fighting, Fire tanker power take off is now widely used in various types of fire vehicle; Powder metallurgy helical gear has low manufacturing cost, excellent mechanical properties, good wear resistance, high temperature and corrosion resistance. In this article the powder metallurgy helical gear is applied on power take off and the finite element method is used on analysis of the characteristic of the transmission gear. The transmission efficiency experiment has been done to prove that powder metallurgy gear transmission has high efficiency, long service life, low manufacturing cost and can enhance the power transmission capability.

We propose a generalized Lanczos method to generate the many-body basis states of quantum lattice models using tensor-network states (TNS). The ground-state wave function is represented as a linear superposition composed from a set of TNS generated by Lanczos iteration. This method improves significantly both the accuracy and the efficiency of the tensor-network algorithm and allows the ground state to be determined accurately using TNS with very small virtual bond dimensions. This state contains significantly more entanglement than each individual TNS, reproducing correctly the logarithmic size dependence of the entanglement entropy in a critical system. The method can be generalized to non-Hamiltonian systems and to the calculation of low-lying excited states, dynamical correlation functions, and other physical properties of strongly correlated systems., 5 pages, 5 figures

Based on the information system characteristics of mine, proposed network architecture design of the mine property. And in this framework based on the design of three-dimensional virtual mine described the application of intelligent management platform. Three-dimensional virtual underground mine that shows the situation, the core application is through remote monitoring system of information exchange between devices (material object communication). Internet of things in the framework of mining three-dimensional virtual reconstruction of mine. On coal mine safety in the production process of human, machine and environment, control elements and their harmony and unity. 3D virtual mine management platform integrates personnel positioning, dust control, gas monitoring, roof pressure monitoring, fan-line monitoring and other subsystems. Platform through the underground mine sensing equipment to conduct various types of monitoring data integration, through the transport layer device to transmit the information to the application layer intelligence processing software platform, the system automatically handles the operational status of each subsystem and the need for safe production under the proper introduction of human factors deal with special event. 3D virtual mine management platform to mining, excavation, transport, ventilation and other safety information quickly and accurately transmitted to the ground operation control center. Underground for the first time on the linkage between systems in case of emergencies, to provide safety for management decision support.

We perform a systematic study of the antiferromagnetic Heisenberg model on the Husimi lattice using numerical tensor-network methods based on Projected Entangled Simplex States (PESS). The nature of the ground state varies strongly with the spin quantum number, $S$. For $S = 1/2$, it is an algebraic (gapless) quantum spin liquid. For $S = 1$, it is a gapped, non-magnetic state with spontaneous breaking of triangle symmetry (a trimerized simplex-solid state). For $S = 2$, it is a simplex-solid state with a spin gap and no symmetry-breaking; both integer-spin simplex-solid states are characterized by specific degeneracies in the entanglement spectrum. For $S = 3/2$, and indeed for all spin values $S \ge 5/2$, the ground states have $120$-degree antiferromagnetic order. In a finite magnetic field, we find that, irrespective of the value of $S$, there is always a plateau in the magnetization at $m = 1/3$., 18 pages, 25 figures;minor changes, refs updated

The ill-posed analytic continuation problem for Green's functions or self-energies can be done using the Pad\'e rational polynomial approximation. However, to extract accurate results from this approximation, high precision input data of the Matsubara Green's function are needed. The calculation of the Matsubara Green's function generally involves a Matsubara frequency summation which cannot be evaluated analytically. Numerical summation is requisite but it converges slowly with the increase of the Matsubara frequency. Here we show that this slow convergence problem can be significantly improved by utilizing the Pad\'e decomposition approach to replace the Matsubara frequency summation by a Pad\'e frequency summation, and high precision input data can be obtained to successfully perform the Pad\'e analytic continuation., Comment: 4 pages, 3 figures

Basing on monthly data from January 2003 to December 2011, Use Multivariate dynamic Markov regime switching model to build the China stock market business cycle index, then use cointegration and error correction model to test its consumptions wealth effect. The test results show that China’s stock market not only has a significant short-term wealth effects, but also has significant long-term wealth effect. However, the coefficient is negative, which is actually a crowding out effect. Using of the autoregressive dynamic distributed lag model, do further empirical analysis and find the asymmetric characteristics of stock market wealth effect in China. The main reason is maybe the substitution effect of investment to consumption larger than those of income effect in China, which may be related to the immature China stock market, investors and instable revenue expectation.

We propose a modified spin-wave theory to study the 1/3 magnetization plateau of the antiferromagnetic Heisenberg model on the kagome lattice. By the self-consistent inclusion of quantum corrections, the 1/3 plateau is stabilized over a broad range of magnetic fields for all spin quantum numbers, S. The values of the critical magnetic fields and the widths of the magnetization plateaus are fully consistent with recent numerical results from exact diagonalization and infinite projected entangled paired states., Comment: 5 pages, 4 figures, accepted in Chinese Physics Letters