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Sample-efficient estimation of entanglement entropy through supervised learning
We explore a supervised machine learning approach to estimate the entanglement entropy of multi-qubit systems from few experimental …
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Quantum State Assignment Flows
This paper introduces assignment flows for density matrices as state spaces for representation and analysis of data associated with …
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Detecting high-dimensional entanglement in cold-atom quantum simulators
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Optimizing design choices for neural quantum states
Neural quantum states are a new family of variational ansätze for quantum-many body wave functions with advantageous properties in the …
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Quantum State Assignment Flows
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Variational Monte Carlo approach to partial differential equations with neural networks
The accurate numerical solution of partial differential equations (PDEs) is a central task in numerical analysis allowing to model a …
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Detecting continuous variable entanglement in phase space with the $Q$-distribution
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General class of continuous variable entanglement criteria
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Optimizing detection of continuous variable entanglement for limited data
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Pair localization in dipolar systems with tunable positional disorder
Strongly interacting quantum systems subject to quenched disorder exhibit intriguing phenomena such as glassiness and many-body …
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