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Measurement of Long Baseline Neutrino Oscillations and Improvements from Deep Learning
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Measurement of Long Baseline Neutrino Oscillations and Improvements from Deep Learning. |
| 개인저자 | Psihas, Fernanda. |
| 단체저자명 | Indiana University. Physics. |
| 발행사항 | [S.l.]: Indiana University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 278 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-11B(E). Dissertation Abstract International |
| ISBN | 9780438065604 |
| 학위논문주기 | Thesis (Ph.D.)--Indiana University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Adviser: Mark D. Messier. |
| 요약 | NOvA is a long-baseline neutrino oscillation experiment which measures the oscillation of muon neutrinos from the NuMI beam at Fermilab after they travel through the Earth for 810 km. In this dissertation I describe the operations and monitoring |
| 요약 | The CNN single particle identifier achieves 65%, 73%, 74%, 83%, and 45% efficiency and 81%, 71%, 86%, 73%, and 45% purity for electrons, photons, muons, protons, and pions, respectively, with no additional selection. The identification of signal |
| 일반주제명 | Physics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
