淺嚐 LHCb 數據分析的滋味 Play around the LHCb Data on Kaggle with SK-Learn and MatPlotLib
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This document discusses data analysis related to high-energy physics experiments at the Large Hadron Collider (LHC), focusing on tools like scikit-learn and matplotlib. It outlines the research goals, such as finding the Higgs boson and exploring particle behavior, while detailing the data processing and storage methods used in these experiments. Additionally, it mentions various Kaggle challenges related to particle physics and provides resources for further exploration of the topics discussed.
淺嚐 LHCb 數據分析的滋味 Play around the LHCb Data on Kaggle with SK-Learn and MatPlotLib
- 1. 淺嚐淺嚐 LHCbLHCb 數據分析的滋味數據分析的滋味 Play around the LHCb Data on Kaggle withPlay around the LHCb Data on Kaggle with SciKit-Learn and MatPlotLibSciKit-Learn and MatPlotLib Yuan CHAO ( 趙元 ) (National Taiwan University, Taipei, Taiwan) PyCon2017 2017/06/09-11
- 3. 研究員 高能物理 使用 OSS 做研究 ...
- 4. 全球 LHC 計算網格 Worldwide LHC Computing Grid (WLCG) 如何分析處理數據？ https://cdsweb.cern.ch/record/1541893 https://www.youtube.com/watch?v=jDC3-QSiLB4
- 7. LHC 周長 27 KM 位於地下 50~150 公尺
- 10. 質子團每秒通過 四千萬次 (40MHz) 平均每次有 15 個對撞
- 17. 事例重建 磁帶長期保存
- 19. 二級資料中心提供實驗學家模擬與分析數據 ( 前 ) 亞洲唯一 一級資料中心 中研院網格中心
- 20. 研究員 高能物理 使用 OSS 做研究 ... Member of CMS Experiment
- 21. 尋找希格斯粒子 Atlas Higgs ML Challenge https://www.kaggle.com/c/higgs-boson $13,000 & 876 teams
- 22. 淺嚐味物理 Search for charged lepton flavour violation https://www.kaggle.com/c/flavours-of-physics Search for new physics on lepton-flavour violation $15,000 & 673 teams
- 25. τ 濤子？ μ 渺子？？ 味物理？ 輕子味不守恆？ –- 請給我五分鐘
- 26. 26 標準模型標準模型 Standard ModelStandard Model ~10-18 m宇宙的尺度 http://htwins.net/scale2/~10-1 m 膠子 光子 W/Z 子 重力子 強作用力 電磁力 弱作用力 重力 夸 克 輕 子 奈米 =10-9 m
- 27. 27 大霹靂大霹靂 The Origin of the UniverseThe Origin of the Universe
- 28. 28 四大問題四大問題 The QuestionsThe Questions LHC was built for the following purposes: 質量的來源 To find the origin of mass... the Higgs boson. 暗物質與暗能量 Looking for the unification.. Super-symmetry as well as other candidates of Dark Mater & Dark energy 反物質的消失 Investigate the mystery of anti-matter disappearance 宇宙初期狀態 Physics at the early stage of the universe: Heavy Ion Collisions and Quark-Gluon Plasma Courtesy of Center for European Nuclear Research (CERN), Geneva, Switzerland.
- 29. 29 Symmetry & Flavor PhysicsSymmetry & Flavor Physics People think the universe is symmetric? E = mc2 Parity violation introduced by T.D. Lee ( 李政道 ) and C.N. Yang ( 楊振寧 ) in 1956. –- 宇稱不守恆 Parity violation seen in a β decay by C.S. Wu ( 吳健雄 ) in 1957. Nobel prize for Lee & Yang. CP violation discovered in Kaon system in 1964. M. Kobayashi and T. Maskawa introduced CP violation in the Standard Model in 1973. –- 電荷・宇稱不守恆 Sanda and Carter pointed out the possibility of CP violation in the B meson system in 1980.
- 30. Prof. Wu's experiment in 1956. Prof. Li and Yang got Nobel Prize in 1957. http://de.wikipedia.org/wiki/Wu-Experiment
- 31. 31 Symmetry & Flavor PhysicsSymmetry & Flavor Physics KTeV experiment at FNAL established the direct CP violation in Kaon system and confirmed by NA48 at CERN in 1999. Belle and BaBar observed indirect CP violation B meson system in 2002. Belle observed the direct CP violation in B → ππ but not confirmed by BaBar in 2004 Belle and BaBar present the evidence of direct CP violation in B → Kππ in 2004. M. Kobayashi ( 小林誠 ) and T. Maskawa ( 益川敏英 ) share the Nobel Prize in 2008 with Y. Nambu ( 南部陽一郎 ). CP violation can't fully explain the Baryon asymmetry problem. → People cont. searching for NP
- 32. Machine Learning is nothing new in HEP People in Tevatron, B- factories, LEP and LHC experiments more or less use MVA in their studies! (LL, LD → BDT, NN, .. → DL?)
- 34. 物理到此為止 ...
- 35. 35 The Kaggle ChallengeThe Kaggle Challenge τ→3μ breaks lepton flavour conservation Basic Data operations Input variables Signal vs. Background Correlations K-S test, CvM test ROC and AUC Machine Learning Algor. Event weight Training and testing AUC score calculation Summary https://www.kaggle.com/c/flavours-of-physics/data Samle Events training.csv mixed MC & data τ→3μ test.csv mixed MC & data τ→3μ check_agre ement.csv mixed MC & data Ds→φ(μμ)π check_corr elation.csv real background data
- 36. 36 The GoalThe Goal Look for the rare events of τ→3μ Classifier not too dependent on MC and data Classifier not too dependent on the τ mass The score is counted using the weighted area under the ROC curve (AUC)
- 37. 37 The K-S TestThe K-S Test The τ→3μ process is not yet observed Signal is made with MC simulation Background are from real data The classifier should not pick up the difference A control channel Ds→φ(μμ)π is used for the similarity The Kolmogorov-Smirnov (KS) test used to evaluate the difference; requiring KS < 0.09 F are the cumulative distribution functions for MC and real data
- 38. 38 The CvM TestThe CvM Test The provided background events are not τ-free Classifier should not too much depend on τ-mass The distribution of τ-mass could be used to extract signal # The Cramer-von Mises (CvM) test is used to test the correlation; requiring CvM-value < 0.002 F are the predictions cumulative distribution functions for all data and data in some mass interval corresponding.
- 39. “Rules… Some of them can be bent, others are to be broken” – Morpheus https://artistotleonline.wordpress.com/category/climax/
- 40. 40 LiveLive DEMO with Jupyter NBDEMO with Jupyter NB Forked from Kaggle challenge package https://github.com/yandexdataschool/flavours-of-physics-start Now following my derived Jupyter notebook https://github.com/yuanchao/flavours-of-physics-start/blob/master/my_baseline.ipynb
- 41. 41 Related URLsRelated URLs LHC computing grid (LCG) and CERN overview video: https://cds.cern.ch/record/2020780 "Higgs ML" Kaggle Challenge https://www.kaggle.com/c/higgs-boson “Flavour of physics” Kaggle Challenge https://www.kaggle.com/c/flavours-of-physics 宇宙的尺度 http://htwins.net/scale2/ Heavy Flavour Data Mining workshop https://indico.cern.ch/event/433556/ Official jupyter NB: https://github.com/yandexdataschool/flavours-of-physics -start My derived jupter NB: https://github.com/yuanchao/flavours-of-physics-start
- 42. 以上 Thank YOU! 謝謝 Remercie de Votre Attention
- 43. 43 Installing Jupyter & SciPyInstalling Jupyter & SciPy Setup a virtual environment (you need python installed before hands) Using pip: $ pip3 install virtualenv You can also use easy_install or apt-get instead Open a terminal Type in the following commands: $ virtualenv -p python3 .scienv $ source .scienv/bin/activate ← activate the environment! $ pip3 install --upgrade pip $ pip3 install jupyter $ pip3 install scipy pandas sklearn ← you get all packages Then start the jupyter notebook server: $ jupyter notebook ← a web page will be loaded automatically Here we go!