Overview
Quantum computing is fast evolving from a research focused towards a market ready technology, with quantum advantage in the near horizon. The algorithms that will lead the charge towards the market unlock are hybrid classical–quantum ones with HPC being at the core of the classical side. In this tutorial, we shall look into two application domains along this — namely combinatorial optimization and quantum chemistry.
Solving combinatorial optimization problems and simulating quantum systems such as molecules and strongly correlated materials are both central challenges in high-performance computing. While classical methods often struggle with exponential scaling, quantum computing offers new algorithmic pathways; however, near-term quantum approaches require careful integration with classical workflows to achieve practical value.
In this tutorial, we present a practical, workflow-oriented view of hybrid quantum–classical computing, focusing on how these approaches can be implemented effectively on real systems. We emphasize what it takes to translate theoretical ideas into practice under realistic constraints such as noise and hardware connectivity. Through guided examples, participants will learn how to design end-to-end workflows that combine quantum circuits with classical and HPC resources, and how to translate these ideas into applications in optimization and simulation. The tutorial emphasizes intuitive understanding and hands-on applicability, making it accessible to students and practitioners looking to get started with quantum-centric supercomputing.
Agenda
| Time (mins) | Topic | Speaker |
|---|---|---|
| 30 | Current landscape of quantum computing | Shesha Raghunathan |
| 80 | Combinatorial optimization on quantum computers | Ritajit Majumdar |
| 80 | Sample-based quantum diagonalization and scalable implementation | Nick Bronn |
| 20 | Synthesis of the workflows and Q&A | All speakers |
Speakers
Ritajit Majumdar
IBM Quantum
Dr. Ritajit Majumdar is a Research Scientist at IBM Quantum, based at the IBM India Research Lab, where he works on advanced large-scale demonstrations using IBM Quantum technologies and was part of the team that demonstrated the first potential quantum advantage candidate from India. He holds a PhD from the Indian Statistical Institute, and was a visiting scholar at the IBM T. J. Watson Research Centre in New York under the Fulbright-Nehru Doctoral Research Fellowship.
Nick Bronn
IBM Quantum
Bio coming soon.
Shesha Raghunathan
IBM Quantum
Bio coming soon.
Resources
Slides, code, and reading materials will be posted here closer to the tutorial date.
Contact
For questions about the tutorial, please reach out to the organizers.
Tutorial presented at HiPC 2026.