Towards improving neutrino telescopes with machine learning | Felix Yu скачать в хорошем качестве

Towards improving neutrino telescopes with machine learning | Felix Yu

Speaker: Felix Yu, 4th year PhD student at Harvard University Neutrino telescopes detect rare particle interactions originating from some of the most extreme environments in the Universe. They achieve this by instrumenting a cubic-kilometer volume of transparent medium with light sensors. Owing to their size and the prevalence of background events, these detectors produce enormous amounts of high-dimensional, highly variable data. Such characteristics pose major challenges for predicting event properties such as direction and energy, particularly with machine learning (ML) methods. In this talk, I will present an efficient point cloud transformer model designed to address these challenges. I will also discuss a self-supervised training strategy that shifts the majority of learning to real data, thereby reducing reliance on simulations and mitigating associated systematic uncertainties. This talk is part of the Liverpool Virtual Seminar Series on Data Intensive Science; more information can be found at https://indico.ph.liv.ac.uk/e/data_sc... #datascience #data #bigdata #neutrino #telescopes #ML