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quant-ph2019
Unsupervised identification of topological order using predictive models
Eliska Greplova, Agnes Valenti, Gregor Boschung +3
Machine-learning driven models have proven to be powerful tools for the identification of phases of matter. In particular, unsupervised methods hold the promise to help discover ne…
quant-ph2019
Hamiltonian Learning for Quantum Error Correction
Agnes Valenti, Evert van Nieuwenburg, Sebastian Huber +1
The efficient validation of quantum devices is critical for emerging technological applications. In a wide class of use-cases the precise engineering of a Hamiltonian is required b…