Quantum simulation for high-energy physics
It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the
US decadal particle-physics community planning, and in fact until recently, this was not …
US decadal particle-physics community planning, and in fact until recently, this was not …
Matrix product states and projected entangled pair states: Concepts, symmetries, theorems
The theory of entanglement provides a fundamentally new language for describing
interactions and correlations in many-body systems. Its vocabulary consists of qubits and …
interactions and correlations in many-body systems. Its vocabulary consists of qubits and …
Fast and converged classical simulations of evidence for the utility of quantum computing before fault tolerance
A recent quantum simulation of observables of the kicked Ising model on 127 qubits
implemented circuits that exceed the capabilities of exact classical simulation. We show that …
implemented circuits that exceed the capabilities of exact classical simulation. We show that …
Tensor networks for complex quantum systems
R Orús - Nature Reviews Physics, 2019 - nature.com
Originally developed in the context of condensed-matter physics and based on
renormalization group ideas, tensor networks have been revived thanks to quantum …
renormalization group ideas, tensor networks have been revived thanks to quantum …
Tensor network algorithms: A route map
MC Bañuls - Annual Review of Condensed Matter Physics, 2023 - annualreviews.org
Tensor networks provide extremely powerful tools for the study of complex classical and
quantum many-body problems. Over the past two decades, the increment in the number of …
quantum many-body problems. Over the past two decades, the increment in the number of …
[HTML][HTML] Hyper-optimized tensor network contraction
J Gray, S Kourtis - Quantum, 2021 - quantum-journal.org
Tensor networks represent the state-of-the-art in computational methods across many
disciplines, including the classical simulation of quantum many-body systems and quantum …
disciplines, including the classical simulation of quantum many-body systems and quantum …
Near-term quantum computing techniques: Variational quantum algorithms, error mitigation, circuit compilation, benchmarking and classical simulation
Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …
and industries including computational science, mathematics, finance, pharmaceutical …
A practical introduction to tensor networks: Matrix product states and projected entangled pair states
R Orús - Annals of physics, 2014 - Elsevier
This is a partly non-technical introduction to selected topics on tensor network methods,
based on several lectures and introductory seminars given on the subject. It should be a …
based on several lectures and introductory seminars given on the subject. It should be a …
Differentiable programming tensor networks
Differentiable programming is a fresh programming paradigm which composes
parameterized algorithmic components and optimizes them using gradient search. The …
parameterized algorithmic components and optimizes them using gradient search. The …
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 …
learning. RBM finds wide applications in dimensional reduction, feature extraction, and …