Machine learning in the search for new fundamental physics
Compelling experimental evidence suggests the existence of new physics beyond the well-
established and tested standard model of particle physics. Various current and upcoming …
established and tested standard model of particle physics. Various current and upcoming …
[HTML][HTML] Applications and techniques for fast machine learning in science
In this community review report, we discuss applications and techniques for fast machine
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …
Search for an excess of electron neutrino interactions in MicroBooNE using multiple final-state topologies
We present a measurement of ν e interactions from the Fermilab Booster Neutrino Beam
using the MicroBooNE liquid argon time projection chamber to address the nature of the …
using the MicroBooNE liquid argon time projection chamber to address the nature of the …
Heavy neutral leptons below the kaon mass at hodoscopic neutrino detectors
Heavy neutral leptons (N) below the kaon mass are severely constrained by cosmology and
lab-based searches for their decays in flight. If N interacts via an additional force, N→ ν e+ e …
lab-based searches for their decays in flight. If N interacts via an additional force, N→ ν e+ e …
[HTML][HTML] Reconstructing the kinematics of deep inelastic scattering with deep learning
We introduce a method to reconstruct the kinematics of neutral-current deep inelastic
scattering (DIS) using a deep neural network (DNN). Unlike traditional methods, it exploits …
scattering (DIS) using a deep neural network (DNN). Unlike traditional methods, it exploits …
Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE …
Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers.
Through geometry, time, and drifted charge from multiple readout wire planes, 3D space …
Through geometry, time, and drifted charge from multiple readout wire planes, 3D space …
Search for an anomalous excess of charged-current quasielastic interactions with the MicroBooNE experiment using Deep-Learning-based reconstruction
We present a measurement of the ν e-interaction rate in the MicroBooNE detector that
addresses the observed MiniBooNE anomalous low-energy excess (LEE). The approach …
addresses the observed MiniBooNE anomalous low-energy excess (LEE). The approach …
Neutral-current background induced by atmospheric neutrinos at large liquid-scintillator detectors. I. Model predictions
J Cheng, YF Li, LJ Wen, S Zhou - Physical Review D, 2021 - APS
The experimental searches for diffuse supernova neutrino background and proton decay in
next-generation large liquid-scintillator (LS) detectors are competitive with and …
next-generation large liquid-scintillator (LS) detectors are competitive with and …
Graph neural network for neutrino physics event reconstruction
A Aurisano, V Hewes, G Cerati, J Kowalkowski, CS Lee… - Physical Review D, 2024 - APS
Liquid argon time projection chamber (LArTPC) detector technology offers a wealth of high-
resolution information on particle interactions, and leveraging that information to its full …
resolution information on particle interactions, and leveraging that information to its full …
Detector signal characterization with a Bayesian network in XENONnT
E Aprile, K Abe, S Ahmed Maouloud, L Althueser… - Physical review D, 2023 - APS
We developed a detector signal characterization model based on a Bayesian network
trained on the waveform attributes generated by a dual-phase xenon time projection …
trained on the waveform attributes generated by a dual-phase xenon time projection …