Session

DescriptionCosmology and particle physics both strive to gain a deeper understanding of the history, the composition and the inner workings of the Universe. While complementary in many aspects, cosmology and particle physics also share many things: they try to find answers to the same open questions, they use similar detectors and analysis techniques, and they both have marvelously precise models. Both disciplines rely heavily on Monte Carlo simulation techniques, they have ever-increasing datasets with planned next-generation experiments, which face yet-unsolved computing challenges related to triggering, data reconstruction and simulation, as well as data storage. Traditional computing approaches are not scaling to these New Challenges and are limiting the physics output. New Computing Paradigms are needed to make progress. Recent developments in machine learning techniques coupled with custom hardware may offer potential directions of improvement. The symposium will highlight several prominent areas in this fast emerging and thriving field with a diverse set of elect international speakers from research Universities both in physics and computer science, research institutes and industry. This rich diversity will provide different angles from which to shine light on the problem for maximum clarity and accessibility of the underlying challenges and the proposed methods to address them.