CHEME 6860

CHEME 6860

Course information provided by the Courses of Study 2020-2021.

Introduces the current status of quantum computing and its applications for artificial intelligence. Topics include Qubit states, entanglement, quantum circuits, Ising model, basics of quantum algorithms, adiabatic quantum computing and quantum annealing, noisy intermediate scale quantum (NISQ) computing, quantum optimization, quantum machine learning and quantum neural network. Learn how to access and use quantum computing resources, set up optimization and machine/deep learning problems to be solved with quantum computing, and develop quantum algorithms for artificial intelligence applications.

When Offered Spring, Summer, Winter.

Prerequisites/Corequisites Preferred prerequisite: CHEME 6800/SYSEN 6800 and CHEME 6880/SYSEN 6880 and/or demonstrated knowledge of optimization and machine/deep learning.

  • Understand the concepts, theory and methods of quantum computing.
  • Demonstrate an ability to apply knowledge of quantum computing for solving practical problems in artificial intelligence.
  • Demonstrate an ability to design and conduct computational experiments using quantum computers, as well as to analyze and interpret data.
  • Identify the engineering application of quantum computing to the optimize engineering systems and analyze large-scale datasets in machine learning.

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Syllabi: none
  •   Regular Academic Session.  Combined with: SYSEN 5860

  • 3 Credits Stdnt Opt

  • 20996 CHEME 6860   LEC 001

    • F Online Meeting
    • Feb 8 - May 14, 2021
    • You, F

  • Instruction Mode: Online