JuliaCon 2026

The explosion in the number of submitted quantum physics papers is placing the scientific publication system under extreme stress. In an effort to address this challenge, I have been experimenting with end-to-end pipelines for the automated numerical verification of claims in quantum physics papers. Given an arXiv preprint, LLM coding agents extract mathematical assertions into a structured knowledge graph, then generate Julia code to numerically check each claim. I will demonstrate this pipeline across three domains: topologically ordered many-body quantum systems (using, e.g., TensorCategories.jl), quantum information theory, and quantum optics (using QuantumOptics.jl). In practice, this system routinely catches small sign errors and gaps in every paper I have studied. LLM coding agents enable automation of workflows that previously would have involved much yak shaving and frustration. As a consequence, time-poor persons with little software engineering expertise (such as myself!) can now employ the amazing cutting-edge tools the Julia community have developed. I will directly address practical challenges including LLM hallucinations in mathematical reasoning, ensuring correctness of generated code, and the gap between symbolic assertions and finite-dimensional numerics.