Session

Third Day - Contributed Talks

13 Oct 2023, 09:40
Procida

Procida

Hotel La Torre, Via Giovanni da Procida, 22 , Procida, Italy

Presentation materials

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  1. David Last (University of Pennsylvania, USA)
    13/10/2023, 09:40
    Abstract for a "contributing talk"
  2. Lu Ren (Colorado Boulder, USA)
    13/10/2023, 10:10
    Abstract for a "contributing talk"

    MicroBooNE is an 85-tonne active volume liquid-argon time projection chamber located in the Booster Neutrino Beam and NuMI beam at Fermilab. It was operational from 2015 to 2020 and collected the largest neutrino-argon interaction dataset to date. The primary goals of MicroBooNE are to understand the low-energy excess observed by MiniBooNE, make precise measurements of neutrino interactions on...

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  3. Miquel Nebot-Guinot (University of Edinburgh)
    13/10/2023, 11:10
  4. Xingyo Zhao (ETHZ, Switzerland)
    13/10/2023, 11:40
  5. Claire Dalmazzone (LPNHE (CNRS))
    13/10/2023, 12:10
  6. Francesco Terranova (Università Milano Bicocca)
    13/10/2023, 12:40
    Abstract for a "contributing talk"

    Monitored neutrino beams represent a powerful and cost effective tool to suppress cross section related systematics for the full exploitation of data collected in long baseline oscillation projects like DUNE and Hyper-Kamiokande. In the last years the NP06/ENUBET project has demonstrated that the systematic uncertainties on the neutrino flux can be suppressed to 1% in an accelerator based...

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  7. Lu Ren (Colorado Boulder, USA)
    13/10/2023, 15:00
    Abstract for a "contributing talk"

    Future neutrino oscillation experiments demand a precise estimation of neutrino flux. The leading flux uncertainty comes from inadequate understanding of primary and secondary hadron-nucleus interactions. The NA61/SHINE experiment at CERN's Super Proton Synchrotron measures various hadron production processes with the goal of reducing the flux uncertainty of current and future...

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  8. Adam Aurisano (University of Cincinnati, USA)
    13/10/2023, 15:50
    Abstract for a "contributing talk"

    The Exa.TrkX Graph Neural Network (GNN) for reconstruction of liquid argon time projection chamber (LArTPC) data is a message-passing attention network over a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all...

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  9. Daisy Kalra (Columbia University)
    13/10/2023, 16:10
    Abstract for a "contributing talk"

    The current and next-generation liquid argon time projection chamber (LArTPC) detectors offer a great opportunity to search for rare, beyond-Standard Model (BSM) physics such as baryon number violation. During operation, these detectors generate high-resolution images of particle interactions, making them well-suited for applying and leveraging deep learning techniques to search for rare...

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  10. Arsenii Gavrikov (Università degli studi di Padova, Italy)
    13/10/2023, 16:30
    Abstract for a "contributing talk"
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