AI summary · arXiv: 2403.00885v1 · physics.ed-ph
Training Computer Scientists for the Challenges of Hybrid Quantum-Classical Computing
The essentials
- The master's course on Hybrid Quantum-Classical Systems at TU Wien aims to bridge the gap in standard computer science curricula
- The course covers topics such as accelerator architectures, HPC workflows, and software stack for quantum accelerated computing
- It includes frontal lectures and practical exercises with access to real or simulated quantum hardware through a cloud frontend
- Intended learning outcomes include understanding differences between quantum and classical computation, analyzing performance improvements of hybrid algorithms, and developing their own using tools like Qiskit
- Course design is outlined in terms of learning outcomes, literature, syllabus, and lecturer profiles
- Evaluation criteria for students are discussed along with expected infrastructure for their work and evaluation of the course itself
- Teaching experience at TU Wien is shared and compared with similar courses offered at other institutions
- Support received for access to quantum computers for future iterations of the course targeting specific learning outcomes
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