Day 4 - Thursday, November 6th
Learning Track: overview on ion trap modality, accelerating DFT calculations using quantum algorithms, accelerating quantum algorithms using GPUs, quantum error correction, quantum kernel estimation
Scaling up ion trap quantum computers and quantum technologies; the case of IonQ
Speaker: Panagiotis Barkoutsos (IonQ) Time: 9:00-10:00
Key topics: ion-trap technology and the updated roadmap of IonQ, scalability beyond qubits and qubit registers, quantum technologies in the industry and how they can be used from an end user perspective
Atomistic simulations on quantum accelerated supercomputing
Speaker: Karim Elgammal (ENCCS/RISE, SE), Marc Maußner (infoteam, DE) Time: 10:00-10:40
An overview on Applications of quantum computing to atomistic simulations and materials science. This session explores how quantum algorithms can enhance Density Functional Calculations (DFT) electronic structure calculations, with practical examples from materials research.
Coffee break
Time: 10:40-11:00
Accelerated quantum supercomputing using NVIDIA CUDA-Q
Speaker: Esperanza Cuenca-Gómez (NVIDIA) Time: 11:00-12:00
📊 Slides: NVIDIA_Accelerated Quantum Supercomputing_Using_CUDA-Q_Esperanza_Cuenca-Gomez.pdf
🔗 Resources from the Talk:
Getting Started:
Examples and Workflows:
CUDA-Q Extensions (cudaqx):
Quantum Error Correction:
cuQuantum:
GPU-accelerated workloads are increasingly being adopted in heterogeneous quantum-classical architectures. These workloads are used to speed up algorithm run time, to test and implement future parallel QPU workflows, to scale up the size of quantum research, and to deploy workflows where QPUs and GPUs are tightly coupled. This session explains NVIDIA’s vision of accelerated quantum supercomputing, introducing CUDA-Q as the platform for high-performance hybrid quantum-classical computing. Relevant works using CUDA-Q are presented. The session includes code examples on how to use CUDA-Q, including quantum kernels and hybrid quantum-classical applications. Attendees are encouraged to explore CUDA-Q and the resources provided after the session.
Lunch
Time: 12:00-13:00
Quantum error-correction (QEC)
Speaker: Mats Granath (Göteborg University) Time: 13:00-14:00
📄 Lecture Notes: QEC Course 2025.pdf
Introduction to quantum error correction, essential for fault-tolerant quantum computing. This session covers the principles of quantum error correction codes and the requirements for implementing QEC in practical quantum workflows.
Quantum kernel estimation with application to disability insurance
Speaker: Björn Löfdahl (SEB) Time: 14:00-15:00
applications of quantum computing within the financial sector.
Coffee break
Time: 15:00-15:30
Interactive tutorial: Quantum error-correction (QEC) hands-on
Speakers: Moritz Lange (Göteborg University) Time: 15:30-16:30
Hands-on tutorial implementing quantum error correction using repetition codes on IQM quantum hardware. This interactive session provides practical experience with QEC concepts, circuit implementation, and error mitigation techniques.
📓 Download Notebook and Solutions:
📥 Download Notebook - Repetition code on IQM
📄 Download PDF Solutions - Complete solutions for the QEC exercises
🚀 Run Notebook in the Cloud (No Installation Required):
interactive tutorial: Quantum kernel estimation with application to disability insurance
Speakers: Anastasiia Andriievska (RISE), Björn Löfdahl (SEB) Time: 16:30-17:30
Hands-on tutorial on quantum kernel estimation methods applied to real-world financial data analysis. This interactive session demonstrates how quantum machine learning techniques can be applied to disability insurance data using quantum kernels.
📓 Download Notebook:
📥 Download Notebook - Quantum kernel estimation for disability insurance
🚀 Run Notebook in the Cloud (No Installation Required):