Mathematical Foundations of Quantum Computing

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Essential Mathematics for Quantum Computing

This focused guide connects key mathematical principles with their specialized applications in quantum computing, equipping students with the essential tools to succeed in this transformative field. It is ideal for educators, students, and self-learners seeking a strong mathematical foundation to master quantum mechanics and quantum algorithms.

Features

Covers key mathematical concepts, including matrix algebra, probability, and Dirac notation, tailored for quantum computing. Explains essential topics like tensor products, matrix decompositions, Hermitian and unitary matrices, and their roles in quantum transformations. Offers a streamlined introduction to foundational math topics for quantum computing, with an emphasis on accessibility and application.

Authors

Dr. Peter Y. Lee (Ph.D., Princeton University) - Expert in quantum nanostructures with extensive experience in teaching and academic program leadership. James M. Yu (Ph.D., Rutgers University) - Expert in mathematical modeling, applied mathematics, and quantum computing, with extensive teaching experience. Dr. Ran Cheng (Ph.D., University of Texas at Austin) - Specialist in condensed matter theory and an award-winning physicist.