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Presented By: Applied Interdisciplinary Mathematics (AIM) Seminar - Department of Mathematics

AIM Seminar: The Heisenberg limit in quantum algorithms and learning

Yu Tong, Caltech

Abstract: The Heisenberg limit is a fundamental limit imposed by the principles of quantum mechanics. It provides a lower bound of the amount of resources needed to achieve certain precision in an estimation task. Saturating the Heisenberg limit brings practical benefits to quantum algorithms and learning protocols. In this talk I will present two algorithms that saturate the Heisenberg limit in ground state energy estimation and in Hamiltonian learning respectively. No prior knowledge of quantum mechanics or quantum computing is assumed.

The seminar will also be broadcast via Zoom at the link

Meeting ID: 960 2164 6996
Passcode: 034405

Contact: Shravan Veerapaneni

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