Quantum Circuit Design with LLMs

Variational quantum circuits are essential for near term quantum algorithms but designing them involves complex manual trial and error. This project solves this bottleneck by creating an automated agentic framework using Large Language Models to synthesize and optimize quantum circuits. By interacting with quantum simulators in a closed loop the AI agent will debug circuits and minimize gate depth automatically. The main deliverables include custom Orchestral AI tools for quantum simulators an iterative feedback pipeline for hyperparameter tuning and comprehensive benchmarking to uncover novel gate sequences.