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Machine Learning in Particle Physics Anomalies by sandaysan01 is a document available to read on EtoBox.
What is Machine Learning in Particle Physics Anomalies about?
Machine learning is essential in particle physics for analyzing experimental anomalies such as muon g−2 and B-meson decays. It is utilized for event classification, anomaly detection, particle identification, and signal processing, employing various algorithms like neural networks and autoencoders. The integration of ML enhances the efficiency of data analysis and simulation, facilitating the search for new physics beyond the Standard Model.
- Author
- sandaysan01
- Language
- EN