FORGE: A Structural Branch Analysis Method for Complex Systems

Forge is a structural branch analysis method designed to evaluate the robustness of complex systems. Rather than validating a model under stable assumptions, Forge systematically perturbs underlying premises to generate alternative structural scenarios, referred to as branches. By comparing outcomes across independently generated branches, the method identifies convergence patterns that reveal hidden constraints, fragile assumptions, and structurally robust relationships within a system. Forge formalizes this process through a six-stage analytical procedure: premise extraction, structural mapping, assumption perturbation, branch generation, branch evaluation, and cross-branch convergence analysis. In addition to testing robustness, the method can surface emergent implications, referred to as overflow signals, when perturbations reveal latent structural dynamics not present in the original model representation. Because the method operates on structured sets of premises and dependency relations rather than domain-specific variables, Forge is domain-general and can be applied to scientific theories, technological architectures, policy models, and other complex systems where hidden assumptions govern outcomes. The paper situates Forge within existing traditions of robustness analysis, scenario planning, and adversarial reasoning, and demonstrates its application through case studies in theoretical physics and technology architecture. Forge is proposed as a methodological tool for systematically mapping the structural landscape of complex systems and identifying which claims remain stable under assumption perturbation.