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Supervised Learning with Tensor Networks
TLDR
It is demonstrated how algorithms for optimizing tensor networks can be adapted to supervised learning tasks by using matrix product states (tensor trains) to parameterize non-linear kernel learning models.
Supervised Learning with Quantum-Inspired Tensor Networks
TLDR
It is demonstrated how algorithms for optimizing such networks can be adapted to supervised learning tasks by using matrix product states (tensor trains) to parameterize models for classifying images.
The ITensor Software Library for Tensor Network Calculations
TLDR
The philosophy behind ITensor, a system for programming tensor network calculations with an interface modeled on tensor diagram notation, and examples of each part of the interface including Index objects, the ITensor product operator, Tensor factorizations, tensor storage types, algorithms for matrix product state (MPS) and matrix product operator (MPO) tensor networks, and the NDTensors library are discussed.
Towards Quantum Machine Learning with Tensor Networks
TLDR
This work proposes a unified framework in which classical and quantum computing can benefit from the same theoretical and algorithmic developments, and the same model can be trained classically then transferred to the quantum setting for additional optimization.
Interaction effects in topological superconducting wires supporting Majorana fermions
Among the broad spectrum of systems predicted to exhibit topological superconductivity and Majorana fermions, one-dimensional wires with strong spin-orbit coupling provide one of the most promising
Studying Two Dimensional Systems With the Density Matrix Renormalization Group
The density matrix renormalization group (DMRG) is one of the most powerful numerical methods for studying two-dimensional quantum lattice systems, despite a perception that it is only suitable for
Minimally entangled typical thermal state algorithms
We discuss a method based on sampling minimally entangled typical thermal states (METTS) that can simulate finite temperature quantum systems with a computational cost comparable to the ground state
Real-space parallel density matrix renormalization group
We demonstrate how to parallelize the density matrix renormalization group (DMRG) algorithm in real space through a straightforward modification of serial DMRG. This makes it possible to apply at
Corner contribution to the entanglement entropy of an O(3) quantum critical point in 2+1 dimensions
The entanglement entropy for a quantum critical system across a boundary with a corner exhibits a sub-leading logarithmic scaling term with a scale-invariant coefficient. Using a Numerical Linked
Corner contribution to the entanglement entropy of strongly interacting O(2) quantum critical systems in 2+1 dimensions
In a D=2+1 quantum critical system, the entanglement entropy across a boundary with a corner contains a subleading logarithmic scaling term with a universal coefficient. It has been conjectured that
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