Explore the intersection of quantum computing and topological data analysis in this informative tutorial. Delve into the concept of quantum persistent homology and discover how quantum computers can uncover patterns in data that classical TDA algorithms cannot detect. Learn about the potential of quantum computers to significantly reduce execution time and energy consumption in data analysis tasks. Gain insights into the applications of quantum Topological Data Analysis as presented by Péguy Kem-Meka Tiotsop Kadzue, a teaching assistant at the University of Ngaoundere with expertise in Topological Data Analysis, Mathematics of Quantum Information, Algebraic Topology, Data Science, Machine Learning, and Climate Change Sciences.
Overview
Syllabus
Quantum Topological Data Analysis (Part 1) [Péguy Kem-Meka]
Taught by
Applied Algebraic Topology Network
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