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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

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Marin Bukov

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#reinforcement learning Open access Oct 2026

Learning to stabilize nonequilibrium phases of matter with active feedback using partial information

Abstract Recent advances in quantum computing experiments have enabled new pathways for feedback control. Here, we investigate the role of information in interactive quantum many-body dynamics to engineer out-of-equilibrium phases of matter. To this end, we train reinforcement learning agents to prevent entanglement sp...

Giovanni Cemin, Markus Schmitt, Marin Bukov · 0 citations
#reinforcement learning Open access Oct 2026

Reinforcement learning to disentangle multiqubit quantum states from partial observations

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 potential to address outstanding challenges in quantum state preparation and compression, quantum control, and quantum complexity. We present a de...

Pavel Tashev, Stefan Petrov, Matthew T. Diaz et al. · 1 citation

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