In the framework of three-active-neutrino mixing, the charge parity phase, the neutrino mass ordering, and the octant of $θ_{23}$ remain unknown. The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment, which aims to address these questions by measuring the oscillation patterns of $ν_μ/ν_e$ and $\barν_μ/\barν_e$ over a range of energies spanning the first and second oscillation maxima. DUNE far detector modules are based on liquid argon TPC (LArTPC) technology. A LArTPC offers excellent spatial resolution, high neutrino detection efficiency, and superb background rejection, while reconstruction in LArTPC is challenging. Deep learning methods, in particular, Convolutional Neural Networks (CNNs), have demonstrated success in classification problems such as particle identification in DUNE and other neutrino experiments. However, reconstruction of neutrino energy and final state particle momenta with deep learning methods is yet to be developed for a full AI-based reconstruction chain. To precisely reconstruct these kinematic characteristics of detected interactions at DUNE, we have developed and will present two CNN-based methods, 2-D and 3-D, for the reconstruction of final state particle direction and energy, as well as neutrino energy. Combining particle masses with the kinetic energy and the direction reconstructed by our work, the four-momentum of final state particles can be obtained. Our models show considerable improvements compared to the traditional methods for both scenarios.
We study the physics reach of the long-baseline oscillation analysis of the DUNE experiment when realistic simulations are used to estimate its neutrino energy reconstruction capabilities. Our studies indicate that significant improvements in energy resolution compared to what is customarily assumed are plausible. This improved energy resolution can increase the sensitivity to leptonic CP violation in two ways. On the one hand, the CP-violating term in the oscillation probability has a characteristic energy dependence that can be better reproduced. On the other hand, the second oscillation max…
The Deep Underground Neutrino Experiment (DUNE), a 40-kton fiducial mass underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino-flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The recent progress on detection and reconstruction of supernova burst neutrinos in DUNE, including the contribution of the light detection systems are presented.
DUNE will be an underground neutrino oscillation experiment that will perform precision measurements of the PMNS mixing parameters, determine unambiguously the mass ordering and discover leptonic CP violation. It also comprises a rich non-accelerator physics program as the detection of supernova neutrinos, nucleon decay and BSM physics. One of the modules of the DUNE is proposed to be Dual-Phase LArTPC. Inside this module, a light detection system (LDS) is being designed, consisting on an array of photomultiplier tubes and a calibration system based on optical fibers. To fulfil the physics pro…
The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for long-baseline neutrino oscillation studies and for neutrino astrophysics and nucleon decay searches. The Far Detector of DUNE will consist of four 10 kt liquid argon time-projection-chambers (LAr TPC) placed in the Sanford Underground Research Facility (SURF) at 1300 km distance from the neutrino beam at Fermilab. The underground location of the Far Detector, at 4300 m.w.e. depth, is essential to be able to study rare and low-energy processes. DUNE will have a unique sensitivity to the electron neutrino flavor compon…
The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino experiment designed to mainly investigate oscillation parameters, supernova physics and proton decay. Its far detector will be composed of four liquid argon time projection chamber (LArTPC) underground modules, in South Dakota-USA, which will detect a neutrino beam produced at Fermilab, 1300 km away, where a near detector will be in place. The second DUNE far detector module, Vertical Drift, will be a single phase LArTPC with electron drift along the vertical axis with two volumes of 13.5 m x 6.5 m x 60 m dimensions se…
Liquid Argon Time Projection Chambers (LArTPCs) have been selected for the future long-baseline Deep Underground Neutrino Experiment (DUNE). To allow LArTPCs to operate in the high-multiplicity near detector environment of DUNE, a new charge readout technology is required. Traditional charge readout technologies introduce intrinsic ambiguities, combined with a slow detector response, these ambiguities have limited the performance of LArTPCs, until now. Here, we present a novel pixelated charge readout that enables the full 3D tracking capabilities of LArTPCs. We characterise the signal to nois…
We investigate the implications of one light eV scale sterile neutrino on the physics potential of the proposed long-baseline experiment DUNE. If the future short-baseline experiments confirm the existence of sterile neutrinos, then it can affect the mass hierarchy (MH) and CP-violation (CPV) searches at DUNE. The MH sensitivity still remains above 5$σ$ if the three new mixing angles ($θ_{14}, θ_{24}, θ_{34}$) are all close to $θ_{13}$. In contrast, it can decrease to 4$σ$ if the least constrained mixing angle $θ_{34}$ is close to its upper limit $\sim 30^0$. We also assess the sensitivity to …
The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for long baseline neutrino oscillation studies, and for neutrino astrophysics and nucleon decay searches. DUNE will comprise four 10 kton fiducial liquid argon time-projection-chamber (LAr TPC) modules placed at the Sanford Underground Research Facility (South Dakota, USA). One of these modules will profit form the dual phase (DP) technology where the charge is extracted, amplified, and detected in gaseous argon above the liquid surface allowing a fine readout pitch, a low energy threshold, and good pattern reconstructio…
The Deep Underground Neutrino Experiment (DUNE) will be a premier facility for exploring long-standing questions about the boundaries of the standard model. Acting in concert with the liquid argon time projection chambers underpinning the far detector design, the DUNE photon detection system will capture ultraviolet scintillation light in order to provide valuable timing information for event reconstruction. To maximize the active area while maintaining a small photocathode coverage, the experiment will utilize a design based on plastic light guides coated with a wavelength-shifting compound, …
In this paper we explore the potential improvements in neutrino event reconstruction that a 3D pixelated readout could offer over a 2D projective wire readout for liquid argon time projection chambers. We simulate and study events in two generic, idealized detector configurations for these two designs, classifying events in each sample with deep convolutional neural networks to compare the best 2D results to the best 3D results. In almost all cases we find that the 3D readout provides better reconstruction efficiency and purity than the 2D projective wire readout, with the advantages of 3D bei…
Liquid Argon (LAr) is one of the most widely used scintillators in particle detection, due to its low cost, high availability and excellent scintillation properties. A large number of experiments in the neutrino sector are based around using LAr in one or more Time Projection Chambers (TPCs), leading to high resolution three-dimensional particle reconstruction. In this paper, we review and summarise a number of these Liquid Argon Time Projection Chamber (LArTPC) experiments, and briefly describe the specific technologies that they currently employ. This includes single phase LAr experiments (I…
In neutrino experiments, neutrino energy reconstruction is crucial because neutrino oscillations and differential cross-sections are functions of neutrino energy. It is also challenging due to the complexity in the detector response and kinematics of final state particles. We propose a regression Convolutional Neural Network (CNN) based method to reconstruct electron neutrino energy and electron energy in the NOvA neutrino experiment. We demonstrate that with raw detector pixel inputs, a regression CNN can reconstruct event energy even with complicated final states involving lepton and hadrons…
Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is becoming more difficult as the detectors increase in size to reach their physics goals. In liquid argon time projection chambers (TPCs) the charged particles from neutrino interactions produce ionization electrons which drift in an electric field towards a series of collection wires, and the signal on the wires is used to reconstruct the interaction. The MicroBooNE detector currently collecting data at Fermilab has 800…
MicroBooNE (the Micro Booster Neutrino Experiment) is a short-baseline neutrino experiment based on the technology of a liquid-argon time-projection chamber (LArTPC), and has recently completed its first year of data-taking in the Fermilab Booster Neutrino Beam. It aims to address the anomalous excess of events with an electromagnetic final state in MiniBooNE, to measure neutrino-argon interaction cross sections, and to provide relevant R\&D for the future LArTPC experiments, such as DUNE. In these proceedings, we present the first reconstructed energy spectrum of Michel electrons from cosmic …
The energy spectrum of a neutrino beam in the few-GeV region is free of uncertainties from nuclear effects when reconstructed via neutrino-hydrogen interactions. On a multinuclear (hydrogen containing) target such interactions can be extracted using transverse kinematic imbalance. We discuss the prospects of this technique for current experiments.
