| 书目名称 | General Model Independent Searches for Physics Beyond the Standard Model |
| 编辑 | Saranya Samik Ghosh,Thomas Hebbeker,Tobias Pook |
| 视频video | |
| 概述 | Provides an updated overview on the models searching for new physics phenomena beyond the Standard Model.Gives insights into future experimental improvements at the LHC involving machine learning tech |
| 丛书名称 | SpringerBriefs in Physics |
| 图书封面 |  |
| 描述 | .This primer describes the general model independent searches for new physics phenomena beyond the Standard Model of particle physics. First, the motivation for performing general model independent experimental searches for new physics is presented by giving an overview of the current theoretical understanding of particle physics in terms of the Standard Model of particle physics and its shortcomings. Then, the concept and features of general model independent search for new physics at collider based experiments is explained. This is followed by an overview of such searches performed in past high energy physics experiments and the current status of such searches, particularly in the context of the experiments at the LHC. Finally, the future prospects of such general model independent searches, with possible improvements using new tools such as machine learning techniques, is discussed.. |
| 出版日期 | Book 2020 |
| 关键词 | BSM - Beyond Standard Model Physics; Model independent searches in particle physics; Machine learning |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-53783-8 |
| isbn_softcover | 978-3-030-53782-1 |
| isbn_ebook | 978-3-030-53783-8Series ISSN 2191-5423 Series E-ISSN 2191-5431 |
| issn_series | 2191-5423 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 17:01:13
