Aligning Quantum Operators with Large Language Models

This work presents a method for integrating quantum operators into Large Language Models (LLMs) by mapping unitary operators into the LLM's latent space, facilitating the modeling of both quantum and linguistic inputs. The authors demonstrate this approach using Clifford+T circuit synthesis over a Pauli rotation gate set, achieving competitive results with existing methods and showing scalability with training data. This advancement suggests the potential for quantum-aware foundation models capable of interpreting quantum operations, which could significantly impact quantum compilation and algorithm discovery for practitioners in AI and quantum computing.