Report of the 2021 U.S. Community Study on the Future of Particle Physics (Snowmass 2021) Summary Chapter

The 2021-22 High-Energy Physics Community Planning Exercise (a.k.a. ``Snowmass 2021'') was organized by the Division of Particles and Fields of the American Physical Society. Snowmass 2021 was a scientific study that provided an opportunity for the entire U.S. particle physics community, along with its international partners, to identify the most important scientific questions in High Energy Physics for the following decade, with an eye to the decade after that, and the experiments, facilities, infrastructure, and R&D needed to pursue them. This Snowmass summary report synthesizes the lessons learned and the main conclusions of the Community Planning Exercise as a whole and presents a community-informed synopsis of U.S. particle physics at the beginning of 2023. This document, along with the Snowmass reports from the various subfields, will provide input to the 2023 Particle Physics Project Prioritization Panel (P5) subpanel of the U.S. High-Energy Physics Advisory Panel (HEPAP), and will help to guide and inform the activity of the U.S. particle physics community during the next decade and beyond.Comment: 75 pages, 3 figures, 2 tables. This is the first chapter and summary of the full report of the Snowmass 2021 Workshop. This version fixes an important omission from Table 2, adds two references that were not available at the time of the original version, fixes a minor few typos, and adds a small amount of material to section 1.1.

A Roadmap for HEP Software and Computing R&D for the 2020s

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.Peer reviewe

IML Machine Learning Workshop

Deep Convolutional Neural Networks (CNNs) have been widely applied in computer vision to solve complex problems in image recognition and analysis. In recent years many efforts have emerged to extend the use of this technology to HEP applications, including the Convolutional Visual Network (CVN), our implementation for identification of neutrino events. In this presentation I will describe the core concepts of CNNs, the details of our particular implementation in the Caffe framework and our application to identify NOvA events. NOvA is a long baseline neutrino experiment whose main goal is the measurement of neutrino oscillations. This relies on the accurate identification and reconstruction of the neutrino flavor in the interactions we observe. In 2016 the NOvA experiment released results for the observation of oscillations in the ν μ → ν e channel, the first HEP result employing CNNs. I will also discuss our approach at event identification on NOvA as well as recent developments in the application of CNNs for particle tagging at NOvA, event identification at DUNE and other ongoing work

Barium daughter tagging using single molecule fluorescence imaging

<p>A robust observation of neutrinoless double beta decay is currently the only known method to determine the Majorana nature of the neutrino. The detection of the single barium ion produced as a result of the double beta decay of xenon 136 would enable a new class of ultra-low background neutrinoless double beta decay experiments. However, despite more than 20 years of R&D, a credible method to collect and identify individual barium ions in bulk xenon has remained elusive.</p> <p>We will present a recent milestone in barium tagging R&D: single barium dication resolution using the technique of single molecule fluorescence imaging (SMFI). This R&D adapts techniques from biochemistry and microscopy to yield a novel technology with potential to extend the sensitivity of neutrinoless double beta decay searches. Individual ions are resolved with high statistical significance and with super-resolution on the nanometer scale. We will present on recent developments and current status.</p

Muon Energy Reconstruction Through the Multiple Scattering Method in the NOvA Detectors

University of Minnesota M.S. thesis. June 2013. Major: Physics. Advisor: Alec Habig. 1 computer file (PDF); v, 54 pages.Neutrino energy measurements are a crucial component in the experimental study of neutrino oscillations. These measurements are done through the reconstruction of neutrino interactions and energy measurements of their products. This thesis presents the development of a technique to reconstruct the energy of muons from neutrino interactions in the NOvA experiment. This is achieved through the understanding of muon multiple scattering within the NOvA detectors. This technique is particularly useful for estimating energies of muons which escape the detector