From Paper to Program: A Multi-Stage LLM-Assisted Workflow for Accelerating Quantum Many-Body Algorithm Development
📰 ArXiv cs.AI
LLM-assisted workflow accelerates quantum many-body algorithm development by generating LaTeX specifications and constraining code generation
Action Steps
- Generate mathematically rigorous LaTeX specification using LLMs
- Use LaTeX specification as intermediate blueprint to constrain code generation
- Implement tensor network algorithms using the generated code
- Test and validate the implemented algorithms
Who Needs to Know This
Quantum computing researchers and software engineers can benefit from this workflow, as it streamlines the development of quantum many-body algorithms and reduces the time required for implementation
Key Insight
💡 Using LLMs to generate LaTeX specifications can improve the accuracy and efficiency of quantum many-body algorithm development
Share This
💡 Accelerate quantum many-body algorithm development with LLM-assisted workflow!
Key Takeaways
LLM-assisted workflow accelerates quantum many-body algorithm development by generating LaTeX specifications and constraining code generation
Full Article
Title: From Paper to Program: A Multi-Stage LLM-Assisted Workflow for Accelerating Quantum Many-Body Algorithm Development
Abstract:
arXiv:2604.04089v1 Announce Type: cross Abstract: Translating quantum many-body theory into scalable software traditionally requires months of effort. Zero-shot generation of tensor network algorithms by Large Language Models (LLMs) frequently fails due to spatial reasoning errors and memory bottlenecks. We resolve this using a multi-stage workflow that mimics a physics research group. By generating a mathematically rigorous LaTeX specification as an intermediate blueprint, we constrain the codi
Abstract:
arXiv:2604.04089v1 Announce Type: cross Abstract: Translating quantum many-body theory into scalable software traditionally requires months of effort. Zero-shot generation of tensor network algorithms by Large Language Models (LLMs) frequently fails due to spatial reasoning errors and memory bottlenecks. We resolve this using a multi-stage workflow that mimics a physics research group. By generating a mathematically rigorous LaTeX specification as an intermediate blueprint, we constrain the codi
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