Franco Nori

Exploring machine learning's role in analyzing topological properties of photonic lattices.

Exploring how machine learning improves quantum control for reliable computing operations.

Study the impact of quantum phase transitions on light and mechanical interactions.

A look into the fascinating world of quantum phase transitions and superradiance.

Explore the significance of nonclassical states in advancing quantum technologies.

Exploring the intricate interactions between quantum and classical physics in ultrastrong coupling.

Research on reliable two-photon quantum gates offers new potential for quantum computing.

Researchers manipulate topological polaritons within optomechanical ladders for advanced applications.

Researchers examine how light changes behavior in atomic systems during phase transitions.

New methods enable detection of superradiant phase transitions in light-matter systems.

Research unveils new ways to control light and matter interactions in superradiant systems.

Research reveals new control methods for emitting quantum entangled pairs directionally.

Exploring light-matter interactions and the conversion of virtual photons to real.

Exploring the efficiency and potential of quantum heat engines in technology.

Researchers apply machine learning to understand complex wave interactions with materials.

An insight into quantum simulation focusing on Yang-Mills theory and particle interactions.