Problem
Research questions and friction points this paper is trying to address.
quantum software development
experiment tracking
reproducibility
provenance
specialized knowledge
Qlippy: A Retrieval-Augmented GenAI Assistant for Reproducible Quantum Workflows and Experiment Tracking
🤖 AI Summary
为解决量子软件开发中的迭代错误和实验跟踪难题，提出Qlippy系统，通过检索增强的GenAI助手结合领域特定知识库，改进实验跟踪和可重复性。
📝 Abstract
Quantum software development is iterative and error-prone. Noisy hardware and repeated re-execution make experiment tracking, provenance, and reproducibility essential, yet these practices are hard to adopt because of tooling complexity and the specialized knowledge they demand. General-purpose language models can help but tend to hallucinate and lack grounding in domain-specific tooling. We present Qlippy, a retrieval-augmented GenAI assistant embedded in the development environment that grounds its responses in a curated corpus of quantum-software-engineering knowledge. Qlippy explains reproducibility and provenance concepts in context and augments existing Qiskit programs with MLflow-based experiment tracking aligned to the QProv schema. By separating knowledge from model parameters, grounding gives explicit control over the scope and provenance of the assistant's responses and reduces reliance on model scale, which points toward low-cost, privacy-preserving local deployment.
Innovation
Methods, ideas, or system contributions that make the work stand out.
retrieval-augmented
quantum workflows
experiment tracking
grounding
local deployment
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