Annotation
This workshop is designed for academics and research professionals with basic knowledge of quantum computing, strong programming skills, and an intermediate understanding of mathematics (linear algebra, probability theory). Participants typically have experience with high-performance computing (HPC) but limited or no prior exposure to quantum platforms or cloud computing. The primary goal of attendees is to explore practical applications of quantum computing in industry, with a particular focus on optimization, machine learning, and quantum chemistry (e.g., force field calculations and molecular docking). The workshop will include hands-on, intermediate-level activities, such as building simple quantum algorithms, and will emphasize Variational Quantum Algorithms (QAOA and VQE), which are central to Quantum Machine Learning.
Benefits for the attendees, what will they learn
Basics of QC, Variational Quantum Algorithms (VQAs) in Qiskit.
Level
Beginner, intermediate
Language
English
Prerequisites
Linear Algebra, Python
Technical requirements
Running Variational Quantum Algorithms (VQAs) through Qiskit's cloud-based GUI is no longer possible, so you need to install Qiskit locally on your computer.
Go to https://docs.quantum.ibm.com/guides/install-qiskit and follow the instructions there. Install the Qiskit SDK and the Qiskit Runtime client.
If you don't have it yet, go to https://quantum.ibm.com and create an IBMid account. This is because you will need an API Token from there to access IBM quantum computers. Also, of course, you can play with simple quantum circuits in the graphical composer there.
Tutors
Marek Lampart is the Head of the Quantum Computing Lab at IT4Innovations National Supercomputing Center. He earned a Ph.D. in Mathematical Analysis in 2002 and was appointed Professor of Computational and Applied Mathematics in 2021. He is an active researcher in the fields of dynamical systems and quantum computing, with more than 50 published scientific papers and an H-index of 11. His current research interests focus on the applications of quantum computing for solving optimization problems, as well as quantum circuit optimization and quantum game theory.
Jiří Tomčala is a researcher in the Quantum Computing laboratory of the IT4Innovations National Supercomputing Center. He graduated with a degree in Applied Mathematics in 2016 and earned his Ph.D. in Computer Science in 2021. In 2021, 2022, 2023, and 2024, he received the Certificate of Quantum Excellence and Quantum Challenge achievement from IBM Quantum. He also participated as a mentor for quantum computing projects in the PRACE Summer of HPC 2021 and 2022. He is an active publishing researcher in the field of quantum computing and regularly contributes his latest results to scientific conferences and journals. His current research interest lies in the use of quantum computation to solve optimization problems and factorization. Thus, he focuses on variational quantum algorithms and the specific applications of Shor's and Grover's algorithms.
Acknowledgements
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903. The JU receives support from the Digital Europe Programme and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg, Slovakia, Norway, Türkiye, Republic of North Macedonia, Iceland, Montenegro, Serbia. This project has received funding from the Ministry of Education, Youth and Sports of the Czech Republic.
This course was supported by the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90254).
