Towards Scalable Braiding: Topological Superconductivity Unlocked under Arbitrary Magnetic Field Directions in Curved Planar Josephson Junctions

The project is an academic research contribution focused on topological quantum computing (TQC). It addresses a critical hardware bottleneck: the requirement for precise magnetic field alignment in planar Josephson junctions. By introducing 'curved' junction geometries, the authors provide a mathematical and simulated path toward scalable braiding—a necessary step for non-Abelian statistics. From a competitive standpoint, the defensibility is moderate (4) because the value lies in the intellectual property and physics insights rather than a software moat. The 7 forks against 0 stars indicate specialized academic interest where researchers are likely adapting the simulation code for their own studies. Frontier risk is low because this research is deep in the condensed matter physics stack, far removed from the generative AI or cloud-native focuses of OpenAI or Anthropic. Even Google Quantum AI or Microsoft (who are heavily invested in Majorana research) would view this as a foundational scientific contribution to be integrated into their hardware roadmaps rather than a product to compete against. The primary risk is scientific: the realization of stable Majorana Zero Modes remains one of the hardest problems in physics, and the entire approach could be displaced by alternative qubit architectures (like transmon or ion-trap) before it reaches commercial viability.