“You can observe a lot by just watching, embracing AI for physics data”
With large amounts of data, a Higgs boson discovery, and world-leading constraints on an enormous amount of parameters and interactions, the Large Hadron Collider has been a phenomenal tool. However, it is going through a mid-life crisis. More data, more Higgs bosons, and more constraints are not bringing the same excitement that we have had in the past. Much like a midlife crisis, we venture in a new direction to show how AI-driven insights allow us to do new, unprecedented physics measurements, leading to many results, including a mysterious deviation in Higgs boson production at high momentum. We build on this idea and show how, through novel physics measurements and their meaningful integration into AI, we can build new foundational models that exploit our current best knowledge. Building on these ideas, we show how AI-based anomaly detection leads to unprecedented physics searches. We then peer into the future and look at strategies to throttle data acquisition by building on advances in processing technology and AI-based computing. Finally, we show a dedicated path for the broad adoption of AI that can impact astrophysics by showing how these ideas can be used to build an astrophysical pipeline. The result of this work is motivates new directions of research and a path towards a larger scale of automation within physics research.
Host: Ian Moult