Deep learning methods are becoming key in the data analysis of particle physics experiments. One clear example is the improvement of neutrino detection using neural networks. Current neutrino experiments are leveraging these techniques, which, in combination, have exhibited to outperform standard tools in several domains, such as identifying neutrino interactions or reconstructing the...
The IceCube neutrino observatory is a gigaton-scale water Cherenkov detector located at the South Pole instrumented with 5160 optical modules in a cubic kilometer of ice. When a high energy neutrino undergoes deep inelastic scattering, the inelasticity of the interaction is the fraction of energy deposited in the hadronic shower to the incoming neutrino energy. For a muon neutrino event, where...
Convolutional neural networks (CNNs) have seen extensive applications in scientific data analysis, including in neutrino telescopes. However, the data from these experiments present numerous challenges to CNNs, such as non-regular geometry, sparsity, and high dimensionality. In this talk, I will present sparse submanifold convolutions (SSCNNs) as a solution to these issues and show that the...
Training neural networks to operate on three-dimensional trajectories from particle detectors is challenging due to the large combinatorial complexity of the data in three dimensions. Using networks that incorporate Euclidian Equivariance could prove to be very beneficial in reducing the need for data augmentation. Our focus is on data from neutrino experiments using liquid argon time...
MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the measured MiniBooNE low energy excess. The LArTPC technology pioneered by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer...
We present NuGraph2, a Graph Neural Network (GNN) for reconstruction of liquid argon time projection chamber (LArTPC) data, developed as part of the ExaTrkX project. We discuss the network architecture, a multi-head attention message passing network that classifies detector hits according to the particle type that produced them. By utilizing a heterogeneous graph structure with independent...
Cherenkov radiation is widely used in particle physics and astro-physics since its discovery in the early 20th century.
Numerous waterCherenkov detectors have been deployed, with more in preparation,for various physics programs such as nucleon decay search and preciseneutrino measurements. Like all other experiments, efficiently quan-tifying detector systematic uncertainties poses a...
NOvA is a leading long-baseline neutrino experiment. Using neutrinos from the ~900 kW NuMI beam at Fermi National Accelerator Laboratory, with a near detector on site and an 810 km baseline to the far detector, in Ash River, Minnesota, NOvA can probe neutrino oscillations. Both detectors are functionally similar fine-grained segmented calorimeters, which makes the readout well-suited as an...
NOvA is a long-baseline neutrino experiment studying neutrino oscillations with Fermilab's NuMI beam. The experiment consists of two functionally identical detectors formed from plastic extrusions filled with a liquid scintillator for the purpose of observing the disappearance of muon neutrinos and the appearance of electron neutrinos. NOvA's recent oscillation measurements used convolution...
The fidelity of detector simulation is crucial for precision experiments, such as the Deep Underground Neutrino Experiment (DUNE) which uses liquid argon time projection chambers (LArTPCs). We can improve the detector simulation by performing dedicated calibration measurements against controlled real data and then applying them to the simulation. Using conventional calibration approaches,...
Modern neutrino experiments employ hundreds to tens of thousands of photon detectors to detect scintillation photons produced from the energy deposition of charged particles. A traditional approach of modeling individual photon propagation as a look-up table requires high computational resources, and therefore it is not scalable for future experiments with multi-kiloton target volume.
We...
The DUNE experiment expects to make some of the most precise measurements of neutrino oscillation parameters by using a neutrino beam originating at Fermilab and measuring it at the Sanford Underground Research Facility (SURF). To accomplish this, novel techniques are being used in both the near- and far-detector designs. Notably, the Liquid Argon Time Projection Chamber (LArTPC) near-detector...
The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics programme. DUNE consists of a near and far detector in a high power wide band neutrino beam. The Precision Reaction Independent Spectrum Measurement (PRISM) refers to the capacity of part of the...
As the role of machine learning methods in neutrino science expands, it is more and more important to have a reliable estimate of the uncertainty of the predictions of such models. Traditional uncertainty propagation does not capture the aleatoric and epistemic uncertainties intrinsic to these models and cannot characterize the models' robustness to out-of-distribution inputs. This talk...
Seeking to harness the power of generative modeling for neutrino physics, we have successfully generated high-fidelity images of track and shower particle event types. We implemented a diffusion model on the PILArNet public dataset comprising 2D images from a simulated Liquid Argon Time Projection Chamber (LArTPC). In this presentation, I will outline the methodology behind the score-based...
IsoDAR (Isotope Decay-At-Rest) is a state-of-the-art electron antineutrino source currently under development. Chief among the technical innovations that allow IsoDAR to reach an unprecedented 10 mA of 60 MeV protons is the inclusion of a radiofrequency quadrupole; a linear accelerator that pre-bunches and focuses the beam before injection into IsoDAR’s cyclotron. IsoDAR’s exceptionally high...
The nEXO Experiment is a search for neutrinoless double beta decay in 136Xe using a 5-ton liquid xenon time projection chamber. This talk introduces the science and design of nEXO and presents an overview of role machine learning plays in its analysis.
nEXO’s machine learning development currently focuses on the analysis of direct-from-sensor signals. nEXO employs an array of electrodes to...
The nEXO Experiment is a search for neutrinoless double beta decay in 136Xe using a 5-ton liquid xenon time projection chamber. Machine learning is employed in nEXO’s analysis as a deep neutral network discriminator to identify gamma ray backgrounds, which are distinguished from double beta decays due to their high prevalence of multiple interaction sites. This talk provides a deeper overview...
The PandaX-4T experiment aims to search for potential dark matter interactions. With significant technical improvements, PandaX-4T achieves unprecedented sensitivity at the low-energy edge of LXe detectors, opening a new window for observing solar neutrinos. Using commissioning data, two hybrid analyses are carried out to search for dark matter interactions, yielding world-leading results for...
Muon-pair production in $pp$ collisions through the Drell-Yan process provides an important tool for studying the internal quark-gluon structure of the nucleon. Precisely measuring the $\cos2\phi$ asymmetry, where $\phi$ represents the azimuthal angle of the $\mu^{+}\mu^{-}$ pair in the Collins-Soper frame, provides valuable insights into the proton's structure. Conventional methods for...
Next-generation experiments in particle physics necessitate immense computational resources. Quantum Machine Learning (QML) could be a potential solution to mitigate these computational challenges. This talk will illuminate recent advances in QML and discuss our efforts to introduce this budding technology to IceCube. I will detail our methodology for translating classical data into quantum...
The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino experiment currently under construction in China. Its main goals are the mass ordering measurement expected to be determined with a $3\sigma$ confidence level in 6 years and the precise measurement of the oscillations parameters $\theta_{12}$, $\Delta m^2_{21}$ and $\Delta m^2_{31}$ ($\Delta m^2_{32}$) at the per-mil level. To...
Coherent elastic neutrino nucleus scattering (CEvNS) off atomic nuclei, predicted over 45 years ago, was recently observed in 2017 within the COHERENT experiment. With its cross section depending quadratically on the number of neutrons in nuclei, CEvNS surpasses all other known neutrino interaction cross sections for heavy elements. This unique characteristic makes it ideal for monitoring...
RED-100 is a xenon two phase emission detector designed to study coherent elastic neutrino nucleus scattering (CEvNS). In 2021-22 it was deployed at Kalinin NPP (Udomlya, Russia) 19 meters from the reactor core. More information about CEvNS and the RED-100 experiment is presented in the talk “The RED-100 experiment” (Dmitry Rudik) while this talk is about reducing specific background...
In this talk, we present Highly Parallel Inference Technique for Monitoring Anti-Neutrinos (HITMAN), an inference tool that combines the extended maximum likelihood decomposition (EML) with neural ratio estimators (NREs) to produce likelihood functions for optical neutrino detectors of arbitrary geometry and material properties. By employing the EML, HITMAN reduces the input dimension of the...
Deep learning models for reconstruction in LArTPC neutrino data have become ubiquitous and have been successfully applied to real analyses. These models usually have to be trained from scratch depending on the task and do not take into account symmetries or systematic uncertainties.
Following advances in contrastive learning we show how such a method can be applied to sparse 3D LArTPC data,...
The Large Enriched Germanium Experiment for Neutrinoless double-beta Decay (LEGEND) project searches for the lepton-number-violating neutrinoless double-beta (0vbb) decay of Ge-76. By utilizing High Purity Germanium (HPGe) detectors enriched with Ge-76 and immersing them directly into liquid argon (LAr), LEGEND combines the superior energy resolution of germanium detectors with the...
Experiments using the 76Ge isotope have set leading limits in the search for neutrinoless double beta decay, offering insights into the nature of neutrinos and the universe. The LEGEND experiment employs High Purity Germanium (HPGe) detectors for this purpose and dramatically reduces backgrounds using Pulse Shape Analysis (PSA). To enhance the analysis, we propose the implementation of a...
The KamLAND-Zen experiment is a multi-purpose neutrino detector in central Japan, with a broad neutrino science program. KLZ has produced world-leading results in the study of solar, geo, and astophysical neutrinos. Recently, KLZ has also set the world-leading limit on the majorana neutrino mass, the first such limit in the Inverted Mass Ordering region. Machine learning plays a key role in...
The MINERvA experiment studies neutrinos cross sections with different nuclei. Neutrino vertex
recognition plays a key role in reconstructing neutrino interactions. This research aims to enhance
previous Machine Learning neutrino vertex recognition models produced in MINERvA using Deep
Convolutional Neural Networks (DCNN). The approach focuses on extending neutrino interaction
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