Analysis of Ultra-High Energy Muons at INO-ICAL Using Pair Meter Technique

The proposed magnetized Iron CALorimeter (ICAL) detector at India-based Neutrino Observatory (INO) is a large-sized underground detector. ICAL is designed to reconstruct muon momentum using magnetic spectrometers as detectors. Muon energy measurements using magnets fail for high energy muons (TeV range), since the angular deflection of the muon in the magnetic field is negligible and the muon tracks become nearly straight. A new technique for measuring the energy of muons in the TeV range, used by the CCFR neutrino detector is known as the pair meter technique. This technique estimates muon energy by measuring the energy deposited by the muon in several layers of an iron calorimeter through e+ and e− pair production. In this work we have performed Geant4-based preliminary analysis for iron plates and have demonstrated the feasibility to detect very high energy muons (1–1000 TeV) at the underground ICAL detector operating as a pair meter. This wide range of energy spectrum will not only be helpful for studying the cosmic rays in the Knee region which is around 5 PeV in the cosmic ray spectra but also useful for understanding the atmospheric neutrino flux for the running and upcoming ultra-high energy atmospheric neutrino experiments

Study of pion production in νμ\nu_{\mu} interactions on 40^{40}Ar in DUNE using GENIE and NuWro event generators

The study of pion production and the effects of final state interactions (FSI) are important for data analysis in all neutrino experiments. For energies at which current neutrino experiments are being operated, a significant contribution to pion production is made by resonance production process. After its production, if a pion is absorbed in the nuclear matter, the event may become indistinguishable from quasi-elastic scattering process and acts as a background. The estimation of this background is very essential for oscillation experiments and requires good theoretical models for both pion production at primary vertex and after FSI. Due to FSI, the number of final state pions is significantly different from the number produced at primary vertex. As the neutrino detectors can observe only the final state particles, the correct information about the particles produced at the primary vertex is overshadowed by FSI. To overcome this difficulty, a good knowledge of FSI is required which may be provided by theoretical models incorporated in Monte Carlo (MC) neutrino event generators. In this work, we will present simulated events for two different MC generators - GENIE and NuWro, for pion production in $\nu_{\mu}$CC interactions on $^{40}$Ar target in DUNE experimental set up. A brief outline of theoretical models used by generators is presented. The results of pion production are presented in the form of tables showing the occupancy of primary and final state pion topologies with 100$\%$ detector resolution and with kinetic energy detector threshold cuts. We observe that NuWro (v-19.02.2) is more transparent (less responsive) to absorption and charge exchange processes as compared to GENIE (v-3.00.06), pions are more likely to be absorbed than created during their intranuclear transport and there is need to improve detector technology to improve the detector threshold for better results.Comment: 14 pages, 6 figures, 10 table

Nuclear Effects and CP Sensitivity at DUNE

The precise measurement of neutrino-oscillation parameters is one of the highest priorities in neutrino-oscillation physics. To achieve the desired precision, it is necessary to reduce the systematic uncertainties related to neutrino energy reconstruction. An error in energy reconstruction is propagated to all the oscillation parameters; hence, a careful estimation of the neutrino energy is required. To increase the statistics, neutrino-oscillation experiments use heavy nuclear targets like argon (Z=18). The use of these nuclear targets introduces nuclear effects that severely impact the neutrino energy reconstruction which in turn poses influence in the determination of neutrino-oscillation parameters. In this work, we have tried to quantify the presence of nuclear effects on the bounds of the CP phase by DUNE using final state interactions

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 experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found. This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions. This is followed by a high-level overview and organization of technical advances, including an abundance of pointers to source material, which can enable these breakthroughs.In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found. This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions. This is followed by a high-level overview and organization of technical advances, including an abundance of pointers to source material, which can enable these breakthroughs

Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

International audienceThe Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents

The DUNE Far Detector Vertical Drift Technology, Technical Design Report

International audienceDUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation