The question
Does a code within a clearly defined search family outperform standard constructions at a selected noise bias or correlation level?
Why it matters
A useful code search needs more than a promising numerical result. It must establish valid stabilizers, identify logical operators, and make every performance comparison reproducible. A well-characterized negative result can also be a valuable contribution.
What you could investigate
- Generate candidates from binary symplectic generator matrices and check commutation, distance, and logical operators.
- Connect Qiskit PauliList or equivalent data structures to independent syndrome tests and exact coset enumeration.
- Validate with Monte Carlo simulation; consider larger-distance extensions with Stim and PyMatching when feasible.
What you could create
- A tested code-search repository
- A documented search family and performance comparison
- A reusable instructional notebook