Day 5 - Friday, November 7th
Learning Track: Advanced FTQC - HW/SW implementation of QEM and QEC, AI and QC
Quantum Neural Networks (lecture)
Speaker: Stefano Markidis (KTH, SE)
Time: 9:00-10:00
Theoretical foundations of Quantum Neural Networks (QNNs) and quantum machine learning. This lecture covers the principles of quantum-enhanced machine learning, potential quantum advantages, and the mathematical framework underlying quantum neural network architectures.
hands-on QNNs using pennylane for classification (tutorial)
Speaker: Stefano Markidis (KTH, SE)
Time: 10:00-10:40
Practical tutorial on implementing Quantum Neural Networks using PennyLane for classification tasks. Participants will gain hands-on experience with quantum machine learning workflows, from data preparation to model training and evaluation.
Coffee Break
Time: 10:40-11:00
Quantum Reservoir computing
Speaker: Ruben Pariente Bassa (SINTEF, NO)
Time: 11:00-12:00
Hands-on implementation of quantum error correction codes. This tutorial provides practical experience with QEC protocols, error syndrome measurement, and error correction procedures using quantum simulators.
Lunch
Time: 12:00-13:00
Towards 2045: Do we still talk about Quantum superiority?
Format: Panel discussion
Time: 13:00-14:00
Forward-looking panel discussion examining the future of quantum computing through 2045. Experts will discuss the timeline for achieving quantum advantage across different application domains, remaining technical challenges, and the evolution of quantum supremacy to practical quantum advantage.
closing
Time: 14:00-15:00
Wrap-up session summarizing key learnings from the five-day intensive program. Participants will have the opportunity to share insights, discuss future applications of quantum computing in their work, and network with instructors and fellow participants.
Sessions are designed to accommodate multiple learning levels, from beginners to advanced practitioners.