A human-in-the-loop multi-stage LLM workflow with an intermediate technical specification externalizing index conventions and contraction orders enables reliable DMRG code generation that reproduces known entanglement scaling and SPT order in spin chains, succeeding in all tested cases.
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Generalized belief propagation approximates tensor network contractions via hierarchical region messages and fixed-point solutions, demonstrated on Ising, ice, AKLT, and random tensor networks.
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From Paper to Program: Accelerating Quantum Many-Body Algorithm Development via a Multi-Stage LLM-Assisted Workflow
A human-in-the-loop multi-stage LLM workflow with an intermediate technical specification externalizing index conventions and contraction orders enables reliable DMRG code generation that reproduces known entanglement scaling and SPT order in spin chains, succeeding in all tested cases.
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Contracting Tensor Networks with Generalized Belief Propagation
Generalized belief propagation approximates tensor network contractions via hierarchical region messages and fixed-point solutions, demonstrated on Ising, ice, AKLT, and random tensor networks.