Tasks placed in the correct stage.
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Hardware-constrained learning for quantum computing and artificial intelligence
Simulation studio
A hybrid pipeline is split into classical preprocessing, quantum subroutine, and classical post-processing zones.
Task cards such as normalization, gate compilation, parameter optimization, measurement averaging, and output decoding are dragged into the most plausible stage, then scored against cost and orchestration tradeoffs.
Module context
Module 1 simulations make the NISQ-era constraints visible and clarify where the quantum subroutine actually sits inside a hybrid workflow.
Live lab
This studio route isolates a single simulation so the learner can focus on one model, one control surface, and one explanatory framing at a time.
Browser-playable lab
Assign each workflow task to the stage where it belongs and compare orchestration cost against the optimal split.
Controls
Normalization is classical feature preparation before any quantum encoding step.
Encoding decisions are mostly classical because they shape the circuit before execution.
Compilation and routing are classical control tasks around the quantum kernel.
Parameter updates happen after measurements are collected and the optimizer revises the next quantum call.
Shot aggregation and expectation estimation happen after the quantum execution phase.
Decoding maps measurement results back into the classical task space.
Outputs
Tasks placed in the correct stage.
Sum of orchestration cost across all stage choices.
Distance from the best-known labor split.
Optimal hybrid systems keep encoding and compilation classical, treat the quantum routine as a narrow kernel, and move averaging plus optimization back into classical post-processing.
Why this lab matters
Hybrid Labor Split Visualizer sits inside Module 1to reinforce the module's core teaching objective through direct manipulation rather than summary-only reading.
Module 1 simulations make the NISQ-era constraints visible and clarify where the quantum subroutine actually sits inside a hybrid workflow.
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