scottjones03/QEC-Lib

QEC-Lib is a wrapper/integration layer combining existing, well-established components (Stim, PyMatching, Union-Find) with a decoder auto-selection heuristic based on syndrome structure. The core innovation—intelligent routing to appropriate decoders—is incremental. The library has minimal traction (4 stars, 0 forks, 126 days old, zero velocity), indicating no adoption beyond the author. No evidence of novel algorithms, data structures, or theoretical breakthroughs; instead, it provides convenient composition of existing tools. The Python QEC ecosystem is narrow but active (Google, Rigetti, others ship QEC tools), and frontier labs (Google Quantum AI, IBM) are actively developing QEC simulators and decoders. Google's Stim itself is a core dependency, and integrating automated decoder selection is a natural extension of that platform. Frontier labs could trivially add this functionality as a feature within their own quantum-software stacks. The project is a personal/research tool with no community adoption, making it trivially reproducible and defensible against exactly zero competitors. High frontier risk because: (1) QEC is a core competency for Google/IBM/other quantum hardware players, (2) Stim is already Google infrastructure, (3) decoder selection is an algorithmic optimization problem well within frontier-lab reach, and (4) no switching costs or network effects exist.