Argonne Sixth Quantum Computing Tutorial

Argonne National Laboratory will host a free hybrid Sixth Quantum Computing Tutorial on June 26-30, 2023. The tutorial is designed to provide hands-on experience programming QAOA (Quantum Approximate Optimization Algorithm) and QML (Quantum Machine Learning) algorithms on IBM quantum computers and quantum circuit simulators using error correction and mitigation schemes. The Zoom link will be provided once your registration attendance criteria has been confirmed.

Participants will learn the basics of how to formulate and solve combinatorial optimization and quantum machine learning problems using Qiskit. In particular, examples will be provided of how problems can be solved using the QAOA and QML (Quantum Machine Learning) algorithms. We will provide step-by-step instructions on how to solve the problems from the ground up with as little hidden complexity as possible. Each presentation will contain a theory introduction and a hands-on session. For hands-on, we will use Jupyter notebooks posted in the tutorial's GitHub repository. These easily customizable code snippets will allow attendees to skip straight to adapting it to their problems and apply it to their own research.

The recommended way to run the hands-on Jupyter notebooks is using the IBM Quantum Experience web interface. Please create an account here before the tutorial (you might have to create an IBM ID if you do not have one): https://quantum-computing.ibm.com/

Registration is limited to only students, postdocs, and staff members from Argonne National Laboratory, Chicago Quantum Exchange, Fermi National Accelerator Laboratory, JPMorgan Chase & Co organizations, the National Quantum Center Q-NEXT, Northwestern University, University of Chicago, the University of Illinois Urbana-Champaign, and the University of Wisconsin-Madison. Please use your work email when registering.

Learn more and register