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Overview of Learning Structured Quantum States - IPAM at UCLA

Institute for Pure & Applied Mathematics (IPAM) via YouTube

Overview

Explore the fundamental challenges of learning unknown quantum states in this 55-minute lecture by Srinivasan Arunachalam from IBM Research, Almaden. Delve into the complexities of quantum computing theory and practice, focusing on the limitations of quantum state tomography and the potential for more efficient learning models. Discover how structured quantum states and alternative learning approaches can overcome the exponential sample complexity typically required for estimating unknown states. Gain insights into the connections between learning Boolean functions and quantum states, and understand the mathematical aspects of quantum learning that enable more efficient techniques. Recorded at IPAM's Mathematical Aspects of Quantum Learning Workshop at UCLA, this talk provides a comprehensive overview of current research in quantum state learning, suitable for those interested in quantum computing theory and its practical applications.

Syllabus

Srinivasan Arunachalam - Overview of learning structured quantum states - IPAM at UCLA

Taught by

Institute for Pure & Applied Mathematics (IPAM)

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