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Learn about polynomial approximation techniques in quantum computing through this lecture from the Park City Mathematics Institute's Graduate Summer School program. Explore the third part of a series on quantum-inspired algorithms, focusing on approximating multiple elements using polynomials. Delve into the quantum singular value transformation (QSVT) framework, examining its applications in quantum algorithm design and potential quantum speedups for data analysis, machine learning, and quantum simulation problems. Access accompanying lecture notes and problem sets focused on polynomial approximation to enhance understanding of the material. Part of a comprehensive three-week summer program featuring expert-led minicourses on quantum computation, including topics like quantum learning, information theory, error-correcting codes, and the complexity theory of random circuits and Hamiltonians.
