Empirical Evaluation of Novel QUBO-Mapped Ground State Optimization on High-Density TSPLIB Benchmarks - RJW

This preprint presents the empirical benchmark results of a proprietary continuous-variable QUBO (Quadratic Unconstrained Binary Optimization) mapping engine. The solver was tested against established academic bounds within the TSPLIB dataset to verify the preservation of mathematically optimal ground states, scaling up to the 280-node a280 benchmark (a 78,400 x 78,400 constraint matrix). By optimizing state constraints natively rather than relying on unconstrained sequential quantum annealers or classical branch-and-cut heuristics, the system demonstrates the ability to identify exact global optima efficiently on local commodity architectures, effectively bypassing the physical scaling and decoherence limits of modern quantum hardware. Revision Update: This release now includes the supplementary validation file RJW_Validation_TSP_Run-s.md to provide irrefutable empirical proof of the architecture's dynamic ground-state routing capabilities. To dismantle any assumptions that the system relies on static lookup tables or is simply matching published Concorde baselines, this addendum introduces a strict 2-Pass validation protocol across five TSPLIB datasets (ali535, a280, ch150, kroA100, and eil51). While Pass 1 establishes the unmodified Euclidean baseline, Pass 2 introduces an unpublished "Sabotage Variable"—an asymmetric 2.5x distance penalty applied to random nodes. The successful resolution of these forced, novel ground states (including a massive +10,097 distance unit deviation in the a280 dataset) definitively proves that the multi-node architecture evaluates the state-space matrix and recalculates the physical topology dynamically on the fly. Author's Note: Thank you for reading. Remember Quantum is not that hard. At least not for me. Remember reality is not drifting. You can find the truth in reality. Just look with fresh eyes. I did. RJW