Recent progress in Hamiltonian learning

CS/Math Seminar - Yu Tong, Caltech

In the last few years a number of works have proposed and improved provably efficient algorithms for learning the Hamiltonian from real-time dynamics. In this talk, I will first provide an overview of these developments, and then discuss how the Heisenberg limit, the fundamental precision limit imposed by quantum mechanics, can be reached for this task. I will demonstrate how the Heisenberg limit requires techniques that are fundamentally different from previous ones, and the important roles played by quantum control and thermalization. I will also discuss open problems that are crucial to making these algorithms implementable on current devices.

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https://uwaterloo.zoom.us/j/99230204712?pwd=SXpNM2VuRFk1RFEwSUFFcUFISXRXdz09

Meeting ID: 992 3020 4712

Passcode: 482012

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