Map Workloads by Quantum Fit and Readiness
Classify candidate workloads by quantum structural fit and current readiness.
Current experiment readiness Quantum structural fit Low readiness High readiness Low fit High fit Build capability High fit, low readiness Promising structure, but missing data, baselines, expertise, or hardware maturity. Invest in learning assets and watch milestones. tl Learning pilot High fit, high readiness Good first candidate. Define benchmark, baseline, expected measurement, and a decision date. tr Leave classical Low fit, high readiness The work may be valuable, but classical tooling is the right path. Improve data, algorithms, or infrastructure instead. bl
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