most citedAI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes

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cond-mat.mes-hall2026

Learning Hamiltonians for solid-state quantum simulators

Jarosław Pawłowski, Mateusz Krawczyk

We introduce a generalizable framework for identifying effective Hamiltonians directly from experimental data in solid-state quantum systems. Our unsupervised autoencoder-based app…

cond-mat.mes-hall2026★ 1 cited

AI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes

Mateusz Krawczyk, Jarosław Pawłowski

We propose a neural network-based model capable of learning the broad landscape of working regimes in quantum dot simulators, and using this knowledge to autotune these devices - b…