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¹Information Sciences, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
²Donostia International Physics Center, Paseo Manuel de Lardizabal 4, San Sebastián E-20018, Spain
³Department of Applied Physics, Gipuzkoa School of Engineering, University of the Basque Country (UPV/EHU), Plaza Europa 1, San Sebastián 20018, Spain
⁴Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
⁵Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland

^*Contact author: cerezo@lanl.gov

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Articles Citing

Quantum Convolutional Neural Networks are Effectively Classically Simulable

Quantum-inspired machine learning: a survey

Neutrino telescope event classification on quantum computers

Order Parameter Discovery for Quantum Many-Body Systems

Simulating Quantum Circuits with Arbitrary Local Noise Using Pauli Propagation

Efficient Quantum-Enhanced Classical Simulation for Patches of Quantum Landscapes

Pauli Propagation: A Computational Framework for Simulating Quantum Systems

Dual role of low-weight Pauli propagation: A flawed simulator but a powerful initializer for variational quantum algorithms

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware

Variational decision diagrams for quantum-inspired machine-learning applications

Benchmarking quantum devices beyond classical capabilities

Optimal quantum reservoir learning in proximity to universality

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Digital quantum magnetism on a trapped-ion quantum computer

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Quantum computing for computer vision: A comprehensive literature survey

Quantum Computing for Predictive Transport Modeling: A Systematic Literature Review and Future Research Needs

Comparative Analysis Between Classical CNNs and Quantum Convolutional Neural Networks for Cacao Pod Disease Classification

Identifying Dynamical Quantum Phase Transitions With a Migratable Quantum‐Classical Hybrid Neural Network

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