QC6.2 Hybrid Quantum–Classical Workflows for High-Performance Computing

This skill introduces the orchestration and integration of quantum workloads into classical High-Performance Computing (HPC) environments. Learners examine hybrid workflows in which classical computation controls, schedules, and post-processes quantum subroutines. Emphasis is placed on the practical challenges that make quantum workflows distinct from typical HPC jobs, including short-duration quantum executions, frequent classical–quantum interactions, transpilation overhead, probabilistic measurement outcomes and, in error-corrected workflows, classical tasks such as syndrome decoding.

The skill focuses on workflow design, scheduling considerations, and resource management for hybrid quantum–classical pipelines.

• QC4.1 Quantum Programming Toolchains
• QC5.2 Quantum Compilation and Transpilation
• QC5.3 Noise, Error Correction, and Fault Tolerance
• QC6.1 Quantum Simulation on Classical High-Performance Computing Systems

• Explain how hybrid quantum–classical workflows differ from standard HPC workflows, emphasizing short-duration quantum executions and frequent interaction with classical control.
  * Describe the impact of quantum transpilation and compilation on workflow timing and scheduling.
  * Explain how probabilistic measurement outcomes influence iterative or hybrid algorithm execution, including repeated evaluations.
  * Describe the role of on-the-fly classical computations for error mitigation and syndrome decoding in error-corrected workflows.
  * Analyse resource management challenges in hybrid workflows, including latency, throughput, and co-location of quantum and classical resources.
• Explain architectural considerations for orchestrating hybrid quantum–HPC pipelines, including batch submission, queueing, and feedback loops.
  * Evaluate practical trade-offs when embedding quantum subroutines in HPC pipelines, such as job overhead versus algorithmic gain.