Speaker
Description
The NOvA experiment has delivered world-leading neutrino physics results over ten years, enabled by an evolving software and computing infrastructure that has adapted to major technical transitions while maintaining operational stability. This talk discusses how NOvA has integrated modern AI/ML workflows into traditional HEP pipelines and balanced innovation against the demands of continuous physics production.
NOvA's computing evolution demonstrates the importance of flexible architectures that accommodate new methodologies, from traditional reconstruction algorithms to machine learning-based event classification, without disrupting ongoing physics programs. The experiment's experience highlights strategies for planning infrastructure when future requirements cannot be fully anticipated, managing technical debt while pursuing innovation, and maintaining continuity across framework transitions.
This talk will present representative examples of NOvA's computing evolution and discuss lessons applicable to other long-duration experiments navigating similar challenges in rapidly changing computing environments.