4 papers
Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations
Pavel Tashev, Stefan Petrov, Matthew T. Diaz +4
Using partial knowledge of a quantum state to control multiqubit entanglement is a largely unexplored paradigm in the emerging field of quantum interactive dynamics with the potent…
Modeling light-matter coupled systems with neural quantum states
Noe Salmeron, Marin Bukov, Markus Schmitt
Recent advances in cold atom manipulation enable the study of many-body systems where short-range interactions between neighboring atoms coexist with long-range interactions mediat…
Predicting Dynamics from Flows of the Eigenstate Thermalization Hypothesis
Dominik Hahn, David M. Long, Marin Bukov +1
Analytical treatments of far-from-equilibrium quantum dynamics are few, even in well-thermalizing systems. The celebrated eigenstate thermalization hypothesis (ETH) provides a post…
Learning to stabilize nonequilibrium phases of matter with active feedback using partial information
Giovanni Cemin, Markus Schmitt, Marin Bukov
We investigate the role of information in active feedback control of quantum many-body systems using reinforcement learning. Active feedback breaks detailed balance, enabling the e…