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Learn about quantum probe tomography through this 54-minute conference talk that explores how to characterize quantum many-body systems using minimal experimental access. Discover a novel approach to Hamiltonian learning that requires only single local probe access to a small subsystem of a many-body thermal state, addressing the significant gap between theoretical protocols demanding full digital quantum control and practical experimental limitations. Explore how algebraic geometry and smoothed analysis combine to create a provably correct algorithm capable of learning generic Hamiltonians across various physically natural families, even under severely constrained conditions. Understand how this breakthrough demonstrates that robust Hamiltonian learning remains feasible in real-world experimental settings where complete system control is unavailable, with applications spanning physics, chemistry, and materials science. Gain insights into the mathematical foundations that enable parameter extraction from thermal states undergoing time evolution, and examine the implications for advancing quantum characterization techniques in practical quantum systems.
