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Paper · arXiv

Multi-agent Autoformalization of Tensor Network Theory

We build a team of specialized large language-model agents and present an agent-driven workflow for research-level formalization in theoretical physics, with the autoformalization of the fundamental theorem of matrix-product states as a demonstration. The agents, coordinated through a structured mathematical blueprint and periodic human review, orchestrated and executed the full formalization autonomously. For some statements, the agents were able to explore new proof routes that are not part of the standard literature. Along the way the agents produced extensive tensor-network and quantum-information libraries not previously available in Mathlib, Lean's mathematical library. As a physica...

AuthorsSirui Lu, Erickson Tjoa, J. Ignacio Cirac
Primary categoryquant-ph
Published8 July 2026
Last updated at source8 July 2026
quant-phcs.AI
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