Description
A series of presentations alternating between technical and physics topics.
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Rasmus Ørsøe (TUM)06/05/2024, 10:00
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Jeffrey Lazar06/05/2024, 10:15
The detection of high-energy astrophysical neutrinos by IceCube has opened a new window on our Universe. While IceCube has measured the flux of these neutrinos at energies up to several PeV, much remains to be discovered regarding their origin and nature. Currently, measurements are limited by the small sample size of astrophysical neutrinos and by the difficulty of discriminating between...
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Matthias Mayer (TUM)06/05/2024, 11:00
The diffuse supernova neutrino background (DSNB) describes the constant flux of neutrinos from past core-collapse supernovae over the visible universe.
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The upcoming Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton liquid scintillator detector, plans to observe the DSNB through the inverse beta decay (IBD) detection channel.
While other electron anti-neutrino sources will cause... -
Rasmus Ørsøe (TUM)06/05/2024, 11:30
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Tomas Kontrimas (Technische Universität München (TUM))07/05/2024, 09:30
One of IceCube’s major goals is finding the origin of astrophysical high-energy neutrinos. The analysis searching for astrophysical point-like sources of neutrinos in the Northern Sky, using 9 years of events produced by charged-current muon-neutrino interactions, identified the active galaxy NGC1068 as a candidate source of astrophysical neutrinos with a global significance of 4.2 sigma. In...
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Philipp Soldin07/05/2024, 10:00
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Arturo Llorente07/05/2024, 10:45
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07/05/2024, 11:15
Machine learning has revolutionized the analysis of large-scale data samples in high energy physics and greatly increased the discovery potential for new fundamental laws of nature. Specifically, graph neural networks (GNNs), thanks to their high flexibility and expressiveness, have demonstrated superior performance over classical deep learning approaches in tackling data analysis challenges...
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Philipp Eller (TUM)08/05/2024, 09:30
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Inar Timiryasov08/05/2024, 10:00
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Jorge González08/05/2024, 10:45
KM3NeT/ARCA and KM3NeT/ORCA are the new generation of neutrino telescopes located
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in the depths of the Mediterranean Sea. Each comprises a grid of optical sensors that
capture the Cherenkov light emitted by charged particles produced in neutrino interactions.
KM3NeT/ARCA, sensitive to interactions with energies ranging from TeV to PeV, focuses on
cosmic neutrinos, while KM3NeT/ORCA... -
Mr Joschka Birk (University of Hamburg)08/05/2024, 11:15
Foundation models are multi-dataset and multi-task machine learning methods that
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once pre-trained can be fine-tuned for a large variety of downstream applications.
We introduce OmniJet-α, a Transformer-based model designed for tokenized
particle jets, showcasing notable advancements on two fronts.
Firstly, our work shows extensive studies on the encoding (tokenization) quality of
our... -
Jarred Green (MPP)09/05/2024, 09:30
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Oliver Janik09/05/2024, 10:00
The analysis of the diffuse neutrino flux with IceCube is usually done using forward-folding binned likelihood fits. The data is binned using energy and angular information. This binning scheme can be improved by employing a neural network optimized summary statistic. For each event, the network predicts a 1D summary statistic which is then binned for the likelihood fit. The network is...
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Troels Petersen09/05/2024, 11:00
GraphNeT opens up for a host of physics analysis and calibration opportunities to be explored. This talk will try to give an overview of some of the ideas that have been discussed, attempted, and carried out, with a subsequent discussion of the gains, challenges, drawbacks, and results. Three of the main ideas are: Data-MC Calibration, improved Self-Veto, and a GraphNeT neutrino selection...
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Luo Meng09/05/2024, 11:30
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Ashish Narayan
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Ara Ioannisyan