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Coarse-graining renormalization by higher-order singular value decomposition
We propose a novel coarse-graining tensor renormalization group method based on the higher-order singular value decomposition. This method provides an accurate but low computational cost techniqueExpand
Accurate determination of tensor network state of quantum lattice models in two dimensions.
TLDR
A novel numerical method to calculate accurately physical quantities of the ground state using the tensor network wave function in two dimensions and results for the Heisenberg model on a honeycomb lattice agree well with those obtained by the quantum Monte Carlo and other approaches. Expand
Equivalence of restricted Boltzmann machines and tensor network states
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 systemsExpand
Interface-induced superconductivity and strain-dependent spin density waves in FeSe/SrTiO3 thin films.
  • Shiyong Tan, Y. Zhang, +14 authors D. Feng
  • Materials Science, Physics
  • Nature materials
  • 13 January 2013
TLDR
It is demonstrated that the superconductivity occurs when the electrons transferred from the oxygen-vacant substrate suppress the otherwise pronounced SDWs in single-layer FeSe, and the phase diagram of FeSe is mapped out as a function of lattice constant, which contains all the essential physics of Fe-HTS. Expand
Differentiable Programming Tensor Networks
TLDR
This work presents essential techniques to differentiate through the tensor networks contractions, including stable AD for tensor decomposition and efficient backpropagation through fixed point iterations, and removes laborious human efforts in deriving and implementing analytical gradients for Tensor network programs. Expand
Gapless Spin-Liquid Ground State in the S=1/2 Kagome Antiferromagnet.
TLDR
This work applies the formalism of tensor-network states, specifically the method of projected entangled simplex states, which combines infinite system size with a correct accounting for multipartite entanglement to demonstrate the ground state of the nearest-neighbor Heisenberg model is a gapless spin liquid. Expand
Iron-based high transition temperature superconductors
In a superconductor electrons form pairs and electric transport becomes dissipation-less at low temperatures. Recently discovered iron-based superconductors have the highest superconductingExpand
Topological characterization of quantum phase transitions in a spin-1/2 model.
TLDR
The quantum phase transitions of the system at zero temperature are found to be of topological type and can be characterized by nonlocal string order parameters (SOP) and in appropriate dual representations, these SOP become local order parameters and the basic concept of Landau theory of continuous phase transition can be applied. Expand
Orbital Origin of Extremely Anisotropic Superconducting Gap in Nematic Phase of FeSe Superconductor
The iron-based superconductors are characterized by multiple-orbital physics where all the five Fe 3$d$ orbitals get involved. The multiple-orbital nature gives rise to various novel phenomena likeExpand
Second renormalization of tensor-network states.
TLDR
A second renormalization group method is proposed to handle the tensor-network states or models and dramatically reduces the truncation error of the Tensor renormalized group. Expand
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