00:50:21 Nkeiru Ubadike: Event rate: 10^3? 00:51:01 Jan Bernauer: How many channels? 00:52:19 Mary Bishai: About 30K channels per detector 00:53:07 Sergey Nikolaevich Syritsyn: where are SuperK, SNO on this diagram? 00:54:02 Mary Bishai: DUNE detector technical design report:https://iopscience.iop.org/article/10.1088/1748-0221/15/08/T08010 00:58:12 Mary Bishai: Oops off by an order of magnitude its 380K channels per 17 kton detector in DUNE. 01:24:08 Jan Bernauer: Thank you! 01:24:19 Timothy Topolski: Thank you! 01:27:30 Nkeiru Ubadike: Is there a role for citizen science in this data analysis? 01:28:48 Ofer Rind: https://lhcathome.cern.ch/lhcathome/ 01:28:59 Timothy Topolski: Is this like the Mersenne prime search program? 01:29:23 Ofer Rind: That one’s easy: https://opendata.cern.ch/ 01:31:49 Jerome Lauret (he/him): Perhaps initiatives such as TrackML could be also noted as an interresting way to perform a citizen science (anyone can try developing algorithms). 01:32:45 Mary Bishai: We will save and post the chat on indico - so the links and comments will be available for exploring after the lecture as well. Please post as much information as you can. 01:32:59 Timothy Topolski: Thanks 01:33:56 Mary Bishai: https://www.kaggle.com/c/trackml-particle-identification 01:35:37 Mike Sivertz: Do neural networks do a very good job at track finding? 01:35:54 Nkeiru Ubadike: Dumb question but any future for quantum computing? 01:36:15 Mary Bishai: Good questions on ML - lecture on Friday too! 01:36:26 Jerome Lauret (he/him): Define "future" :-D 01:37:11 Mary Bishai: Neural networks for vertex finding - especially in High Lumi LHC 01:37:19 Nkeiru Ubadike: haha, I guess its a long time away 01:38:09 Jerome Lauret (he/him): Yes Quantum is being used in Theory but seems like a long term (not a tomorrow thing). But to be watched ... 01:39:59 Mary Bishai: Higgs boson discovery used a neural network. Here is another challenge from 7 years ago: 01:40:00 Mary Bishai: https://www.kaggle.com/c/trackml-particle-identification 01:40:48 Mary Bishai: Oops https://www.kaggle.com/c/higgs-boson 01:40:57 Karan Kumar: Seems like quantum machine learning is a thing now, I don't know how this work. 01:41:27 Nkeiru Ubadike: Thank you for your answer! 01:41:43 Ye, Esther (STUDENT): ^QML’s also in the development stage at the moment I think 01:43:56 Jerome Lauret (he/him): QML is a thing and we see more and more proposal and tries. We need to observe this field and see the advances and possible breakthrough. There is indeed a class of problems that are QML friendly. 01:47:42 Nkeiru Ubadike: I see. I am quite interested but naive in this area so I wanted to see if there was any connection. Thanks for the exploratory discussion. 01:48:09 Mary Bishai: Higgs discovery paper with description of signals and neural network utlilization : https://arxiv.org/pdf/1207.7214.pdf 01:48:22 brynna Moran: Thank you! 01:48:24 David Wan: Thank you 01:48:24 Ye, Esther (STUDENT): Thank you! 01:48:26 Andrea: Thank you! 01:48:31 Karan Kumar: Thank you!