Mathematical Foundations of Quantum Computing: A Scaffolding Approach. Cet article n’est pas disponible.Mathematical Foundations of Quantum Computing: A Scaffolding Approach

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.

Please note: Because of Amazon's page restrictions for hardcover printings, the 18-page "Key Formulas and Concepts" appendix has been omitted from this edition.

Dr. Peter Y. Lee holds a Ph.D. in Electrical Engineering from Princeton University. His research at Princeton focused on quantum nanostructures, the fractional quantum Hall effect, and Wigner crystals. Following his academic tenure, he joined Bell Labs, making significant contributions to the fields of photonics and optical communications and securing over 20 patents. Dr. Lee's multifaceted expertise extends to educational settings; he has a rich history of teaching, academic program oversight, and computer programming.

Dr. James M. Yu earned his Ph.D. in Mechanical Engineering from Rutgers University at New Brunswick, specialized in mathematical modeling and simulation of biophysical phenomena. Following his doctorate studies, He continued to conduct research as a postdoctoral associate at Rutgers University. Currently, he is a faculty member at Fei Tian College, Middletown where he dedicates to teaching mathematics, statistics, and computer science.

Dr. Ran Cheng earned his Ph.D. in Physics with a focus on theoretical condensed matter physics from the University of Texas at Austin. Following his doctoral studies, he furthered his inquiry into magnetic materials and nanostructures as a postdoctoral researcher at Carnegie Mellon University. He is now a faculty member at the University of California, Riverside, where he actively explores three core research domains: spintronics, topological materials, and low-dimensional quantum magnets. A recognized pioneer in the burgeoning field of antiferromagnetic spintronics, Dr. Cheng was honored with the DOD MURI award alongside a cadre of distinguished physicists, furthering advancements in this innovative domain.