Dissipation-enabled Bosonic Hamiltonian Learning via Information Propagation Bounds

Watch a 24-minute conference talk from the Theory of Quantum Computation (TQC 2024) conference exploring groundbreaking research in bosonic Hamiltonian learning. Delve into novel approaches for characterizing quantum systems through a presentation that introduces a moment criterion for m-mode Hamiltonians and proposes an enhanced learning procedure utilizing dissipation. Learn how coherent states and heterodyne detection can be leveraged to efficiently learn bosonic Hamiltonians, with particular focus on an innovative protocol involving projected coherent state preparation and dissipative regularization. Discover new Lieb-Robinson type bounds for bosonic Hamiltonian evolution and understand their implications for continuous variable systems. The presentation, delivered at OIST in Japan, offers valuable insights for researchers and students working in quantum information science, particularly those interested in theoretical approaches to quantum system characterization and benchmarking.