Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.
Ciccarello, Collision models in quantum optics, Quan- tum Meas
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Getting large-scale quantum neural networks ready for quantum hardware
Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.