This skill introduces the practical implementation of variational quantum algorithms as hybrid quantum-classical workflows. Learners implement a simple variational algorithm, combining parameterised quantum circuits with a classical optimisation loop. Emphasis is placed on understanding the end-to-end execution pattern, including repeated circuit evaluation, expectation value estimation, and parameter updates.

The focus is on workflow comprehension and practical execution rather than mathematical derivation or performance tuning.

• QC3.1 Conceptual Overview of Variational Algorithms
• QC4.1 Quantum Programming Toolchains

• Describe the end-to-end workflow of a variational quantum algorithm.
• Implement a parameterised quantum circuit using a quantum programming framework.
• Execute a hybrid quantum-classical loop involving circuit execution and classical optimisation.
• Compute and interpret expectation values used to guide parameter updates.
• Distinguish the practical execution workflow of a variational algorithm from that of a gate-model algorithm.