PHYS 437: Quantum Computing for Scientists

Target Audience: M.S. and Ph.D. students in Natural Sciences.

This course serves as an introduction to the practical applications of quantum computing in physics and chemistry. It also serves as an introductory and hands-on experience on the new and growing field of quantum thermodynamics, since current generation of quantum computers are better treated as open quantum systems.
It is specifically designed for students who recognize the growing importance of the use of quantum processor units for science. Students are expected to be versed in quantum physics, dynamics and quantum information theory.

Course Code: 2300437

Course Title: Quantum Computing for Scientists

Course Type: Elective

Instructor: Assoc. Prof. Dr. Barış Malcıoğlu

Instructional Methods:

  • Interactive lectures with live coding demonstrations.

  • Hands-on sessions with Jupyter notebooks.

  • Problem-solving sessions.

Assessment Methods:

  • Assignments/Midterm (50%): Regular programming assignments to reinforce concepts and build proficiency, plus a theoretical midterm.

  • Final Project (50%): A small project involving the implementation and analysis of a quantum algorithm or protocol for an actual QPU (must be designed for an open quantum system).

Prerequisites: A basic familiarity with Python programming, quantum physics, and quantum information theory.

Contents:

  1. A review of currently available Quantum Processor Unit technologies, HPC+QPU system integration models.

  2. A quick reminder of the circuit model, and some alternatives.

  3. Concept of transpilation.

  4. Density matrices and their use in dealing with QPU hardware.

  5. Error correction and mitigation

  6. Noise as a resource, quantum thermodynamics view of QPUs

  7. Time crystals.