Reality: Quantum advantage - quantum computers outperforming classical computers - is not yet universal and remains workload-specific. Quantum advantage has been demonstrated in very limited, specialized contexts like certain optimization problems. Several “Quantum Advantage” demonstrations show solving a specially-designed problem that has little or no practical use. HPC managers are advised to take these demonstrations with a grain of salt. Benchmarking results illustrate the potential for quantum advantage for targeted applications but emphasize the necessity of careful workload selection and hybrid execution strategies.

Separating terms that fuel confusion

• Quantum advantage: A quantum system beats the best feasible classical method on a specific, well-defined task (ideally of practical interest).
• Quantum supremacy: A device performs some task no classical computer can feasibly match, regardless of usefulness.
  NISQ-era hardware can show beyond-classical behavior yet still fall short of broad, application-level advantage.  

Why the myth persists

• Headlines vs. workloads: Landmark experiments (e.g., random-circuit sampling) are scientific milestones, not general-purpose wins for optimization, ML, or simulation.  
• Moving classical baselines: Classical simulation methods continually improve, sometimes narrowing or reframing earlier claims.  
• Inconsistent benchmarks: Many “advantage” reports omit end-to-end metrics (compile, queue, execute, post-process) that determine time-to-answer in HPC settings.  

What this means for HPC managers

Treat “advantage” claims as workload hypotheses to test, not facts to accept.

Prioritize KPIs that reflect production reality

• Time-to-answer on your instances (including queueing, compilation, execution, and post-processing).
• Solution quality vs. best classical baseline (gap, variance, and reproducibility).
• Throughput (circuits/sec, jobs/hour) under your scheduler.
• Stability window (how often the system needs to be re-calibrated).

How to read vendor claims

• “Quantum advantage achieved.” Ask: On what task, with what classical baseline, and what end-to-end time-to-answer?
• “Utility before fault tolerance.” Great—for which problems?  
• “Supremacy/random-circuit sampling.” Important milestone, but it is relevant for your workload?.

Where to look for near-term value

• Physics-like simulation where analog or hybrid analog-digital modes map closely to the Hamiltonian.
• Combinatorial optimization where problem graphs align with device connectivity and hybrid loops can reduce wall-clock iterations.
• Sampler/estimator subroutines that can be cleanly embedded in classical pipelines.

Bottom line

Quantum advantage is not one thing you “have” or “don’t have.” It is workload-specific and pipeline-dependent. Use application-oriented benchmarks, insist on end-to-end time-to-answer, and plan for hybrid execution. This keeps you grounded while the science advances—and positions your HPC environment to benefit as genuine, domain-level advantages emerge.  

‍

‍