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Found 14 papers, 10 papers with code
Entanglement and Tensor Networks for Supervised Image Classification
For that purpose, we propose a plausible candidate state $|\Sigma_{\ell}\rangle$ (built as a superposition of product states corresponding to images in the training set) and investigate its entanglement properties.
Anomaly Detection with Tensor Networks
Originating from condensed matter physics, tensor networks are compact representations of high-dimensional tensors.
TensorNetwork on TensorFlow: Entanglement Renormalization for quantum critical lattice models
We use the MERA to approximate the ground state wave function of the infinite, one-dimensional transverse field Ising model at criticality, and extract conformal data from the optimized ansatz.
Computational Physics
TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor Networks
TensorNetwork is an open source library for implementing tensor network algorithms in TensorFlow.
TensorNetwork: A Library for Physics and Machine Learning
TensorNetwork is an open source library for implementing tensor network algorithms.
Continuous matrix product states for non-relativistic quantum fields: a lattice algorithm for inhomogeneous systems
Given the continuum Hamiltonian $H$, we consider a sequence of discretized Hamiltonians $\{H(\epsilon_{\alpha})\}_{\alpha=1, 2,\cdots, p}$ on increasingly finer lattices with lattice spacing $\epsilon_1 > \epsilon_2 > \cdots > \epsilon_p$.
Quantum Gases
Topological conformal defects with tensor networks
On the torus, the partition function $Z_{D}$ of the critical Ising model in the presence of a topological conformal defect $D$ is expressed in terms of the scaling dimensions $\Delta_{\alpha}$ and conformal spins $s_{\alpha}$ of a distinct set of primary fields (and their descendants, or conformal towers) of the Ising CFT.
Strongly Correlated Electrons Statistical Mechanics High Energy Physics - Theory Quantum Physics
NCON: A tensor network contractor for MATLAB
This article presents a MATLAB function ncon(), or "Network CONtractor", which accepts as its input a tensor network and a contraction sequence describing how this network may be reduced to a single tensor or number.
Computational Physics Strongly Correlated Electrons Quantum Physics
Global symmetries in tensor network states: symmetric tensors versus minimal bond dimension
In this paper we explore the trade-off between using a tensor network N with minimal bond dimension \chi^{min} and a tensor network N_{sym} made of symmetric tensors, where the minimal bond dimension \chi^{min}_{sym} might be larger than \chi^{min}.
Strongly Correlated Electrons
Perfect Sampling with Unitary Tensor Networks
Tensor network states are powerful variational ans\"atze for many-body ground states of quantum lattice models.
Strongly Correlated Electrons Quantum Physics
Tensor network states and algorithms in the presence of a global U(1) symmetry
Tensor network decompositions offer an efficient description of certain many-body states of a lattice system and are the basis of a wealth of numerical simulation algorithms.
Strongly Correlated Electrons
Tensor network decompositions in the presence of a global symmetry
Tensor network decompositions offer an efficient description of certain many-body states of a lattice system and are the basis of a wealth of numerical simulation algorithms.
Strongly Correlated Electrons
Mixed-state dynamics in one-dimensional quantum lattice systems: a time-dependent superoperator renormalization algorithm
We present an algorithm to study mixed-state dynamics in one-dimensional quantum lattice systems.
Strongly Correlated Electrons Quantum Physics
Efficient classical simulation of slightly entangled quantum computations
We present a scheme to efficiently simulate, with a classical computer, the dynamics of multipartite quantum systems on which the amount of entanglement (or of correlations in the case of mixed-state dynamics) is conveniently restricted.
Quantum Physics
