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A Call to Qiskit Advocates: Help Test Quantum Advantage

Posted on September 14, 2026 by

Quantum advantage becomes more credible when other people can try to break it.

We invite Qiskit Advocates, students, researchers, and independent builders to examine a set of small, reproducible quantum-workflow benchmarks. The aim is not to declare victory over classical computing. It is to make concrete claims challengeable: run the same circuits, improve a baseline, find a better observable, or identify where a timing comparison is not fair.

What is available to test?

The Pro Student Quantum Advantage List brings together six student-scale projects spanning Fermi-Hubbard dynamics, non-Abelian hadron dynamics, an 80-qubit Operator Loschmidt Echo, Random Graph Sampling, QOS-inspired quantum machine learning, and Floquet-Ising dynamics.

Each entry specifies its task, hardware route, timing scope, classical comparison, and claim boundary. Some show a local time-to-answer or runtime separation under declared resources. Others remain diagnostic or incomplete. That distinction matters: a faster quantum runtime is not automatically a general, asymptotic, or matched-accuracy quantum advantage.

A useful contribution can be negative

An independent replication that finds a stronger classical method is valuable. So is a result that exposes a mismatched observable, an unconverged tensor-network baseline, missing service overhead, or insufficient output-quality validation. The goal is transparent progress, not protecting a headline.

For example, the Random Graph workflow has a full 70-qubit hardware sampling run, but its output-quality comparison is still open. The QOS-inspired PBMC68k route has a measured local time separation for feature generation, while its small test set and unconverged MPS reference prevent a broader predictive-advantage claim. These are invitations to improve the evidence.

How to participate

  • Choose one published workflow and reproduce a clearly stated part of it.
  • Keep the task, resource scope, and accuracy target explicit.
  • Share a stronger baseline, a validation check, or a failure mode with enough detail to investigate it.
  • Link the result to the relevant Edukaizen project page or source repository.

The most useful outcome is a public record that gets stricter over time: confirmed separations where they survive scrutiny, and corrected or withdrawn claims where they do not.

Source context: A call to fellow Qiskit Advocates: help us test quantum advantage.

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