Quantum computing is an emerging paradigm that leverages principles of quantum mechanics to provide known computational speedups for certain classes of problems and may offer advantages for others. This node introduces learners to the foundations of quantum information, quantum programming, and the integration of quantum resources into High-Performance Computing (HPC) workflows. By covering foundational principles, algorithms, programming, hardware, simulation, and hybrid and alternative computational models, this branch prepares learners for both conceptual understanding and practical experimentation.

External: * Basic linear algebra
* Introductory quantum mechanics (helpful but not required)

• Analyse how quantum information is represented, manipulated, and measured within the gate-based model of quantum computation.
• Evaluate representative quantum algorithms and protocols in terms of their computational principles and advantages relative to classical approaches.
• Compare variational, hybrid quantum-classical, and quantum-inspired methods in terms of their workflows, applicability, strengths, and limitations.
• Assess quantum programming frameworks and workflows for implementing and executing gate-model and variational algorithms.
• Assess how hardware characteristics, compilation, noise, and fault-tolerance requirements constrain the practical execution of quantum computations.
• Assess the capabilities and practical limitations of classical quantum simulation on HPC systems.
• Assess the integration and effectiveness of quantum resources within HPC workflows relative to appropriate classical baselines.
• Assess quantum annealing and adiabatic approaches in terms of their computational model, problem suitability, and practical constraints.

• QC1 Quantum Computing Principles
• QC2 Quantum Algorithms
• 3
• 4
• QC5 Quantum Hardware and Architectures
• QC6 Integration of Quantum and High-Performance Computing
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