Quantum neural network states: A brief review of methods and applications
One of the main challenges of quantum many‐body physics is the exponential growth in the
dimensionality of the Hilbert space with system size. This growth makes solving the …
dimensionality of the Hilbert space with system size. This growth makes solving the …
Efficient representation of topologically ordered states with restricted Boltzmann machines
Representation by neural networks, in particular by restricted Boltzmann machines (RBMs),
has provided a powerful computational tool to solve quantum many-body problems. An …
has provided a powerful computational tool to solve quantum many-body problems. An …
Efficient machine-learning representations of a surface code with boundaries, defects, domain walls, and twists
Machine-learning representations of many-body quantum states have recently been
introduced as an ansatz to describe the ground states and unitary evolutions of many-body …
introduced as an ansatz to describe the ground states and unitary evolutions of many-body …
Expressive power of complex-valued restricted Boltzmann machines for solving nonstoquastic Hamiltonians
CY Park, MJ Kastoryano - Physical Review B, 2022 - APS
Variational Monte Carlo with neural network quantum states has proven to be a promising
avenue for evaluating the ground-state energy of spin Hamiltonians. However, despite …
avenue for evaluating the ground-state energy of spin Hamiltonians. However, despite …
Entanglement area law for shallow and deep quantum neural network states
A study of the artificial neural network representation of quantum many-body states is
presented. The locality and entanglement properties of states for shallow and deep quantum …
presented. The locality and entanglement properties of states for shallow and deep quantum …
Neural-network quantum states for spin-1 systems: Spin-basis and parameterization effects on compactness of representations
MY Pei, SR Clark - Entropy, 2021 - mdpi.com
Neural network quantum states (NQS) have been widely applied to spin-1/2 systems, where
they have proven to be highly effective. The application to systems with larger on-site …
they have proven to be highly effective. The application to systems with larger on-site …
Unitary-coupled restricted Boltzmann machine ansatz for quantum simulations
Neural-network quantum state (NQS) has attracted significant interests as a powerful wave-
function ansatz to model quantum phenomena. In particular, a variant of NQS based on the …
function ansatz to model quantum phenomena. In particular, a variant of NQS based on the …
Electric-magnetic duality and Z2 symmetry enriched Abelian lattice gauge theory
Kitaev's quantum double model is a lattice realization of Dijkgraaf-Witten topological
quantum field theory (TQFT), its topologically protected ground state space has broad …
quantum field theory (TQFT), its topologically protected ground state space has broad …
A Knowledge Compilation Map for Quantum Information
Quantum computing is finding promising applications in optimization, machine learning and
physics, leading to the development of various models for representing quantum …
physics, leading to the development of various models for representing quantum …
Electric-magnetic duality of symmetry enriched Abelian lattice gauge theory
Z Jia, D Kaszlikowski, S Tan - arXiv preprint arXiv:2201.12361, 2022 - arxiv.org
Kitaev's quantum double model is a lattice gauge theoretic realization of Dijkgraaf-Witten
topological quantum field theory (TQFT), its topologically protected ground state space has …
topological quantum field theory (TQFT), its topologically protected ground state space has …