QC Lab: Modular Cyberinfrastructure for Quantum–Classical Simulations of Excited-State Dynamics
Excited-state dynamics underpins quantum information science and the next generation of (opto)electronics, yet its simulation tools trail far behind those for static electronic structure. Quantum–classical (QC) dynamics is a family of simulation techniques that optimally balance accuracy and cost, but the available cyberinfrastructure is fragmented across incompatible, often unpublished codes. QC Lab addresses this: an open-source Python package that decomposes simulations into modular algorithms and models, so any method works with any model by construction. New methods reuse existing components and add only what differs. The same modularity makes QC Lab AI-legible: because contributions are compact, strictly formatted plugins, generative AI can assist the documentation and contribution-review work that typically bottlenecks community cyberinfrastructure, while the scientific core stays human-authored and behind human review. We are building convention-grounded, AI-assisted tooling for both. Distributed via PyPI under Apache 2.0 with public documentation and contribution workflows, QC Lab lays the foundation for a sustainable, community-driven cyberinfrastructure for excited-state dynamics.