Electron Cloud Measurements in Fermilab Booster

Fermilab Booster synchrotron requires an intensity upgrade from 4.5x1012 to 6.5x1012 protons per pulse as a part of Fermilab's Proton Improvement Plan-II (PIP-II). One of the factors which may limit the high-intensity performance is the fast transverse instabilities caused by electron cloud effects. According to the experience in the Recycler, the electron cloud gradually builds up over multiple turns inside the combined function magnets and can reach final intensities orders of magnitude greater than in a pure dipole. Since the Booster synchrotron also incorporates combined function magnets, it is important to measure the presence of electron cloud. The presence or apparent absence of the electron cloud was investigated using two different methods: measuring bunch-by-bunch tune shift by changing the bunch train structure at different intensities and propagating a microwave carrier signal through the beampipe and analyzing the phase modulation of the signal. This paper presents the results of the two methods and corresponding simulation results conducted using PyECLOUD software.Comment: International Particle Accelerator Conference 202

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a $\nu_\mu$ charged current neutral pion data samples

First Measurement of νμ\nu_{\mu} Charged-Current π0\pi^{0} Production on Argon with a LArTPC

We report the first measurement of the flux-integrated cross section of $\nu_{\mu}$ charged-current single $\pi^{0}$ production on argon. This measurement is performed with the MicroBooNE detector, an 85 ton active mass liquid argon time projection chamber exposed to the Booster Neutrino Beam at Fermilab. This result on argon is compared to past measurements on lighter nuclei to investigate the scaling assumptions used in models of the production and transport of pions in neutrino-nucleus scattering. The techniques used are an important demonstration of the successful reconstruction and analysis of neutrino interactions producing electromagnetic final states using a liquid argon time projection chamber operating at the earth's surface

Novel event classification based on spectral analysis of scintillation waveforms in Double Chooz

Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level

Rejecting cosmic background for exclusive neutrino interaction studies with Liquid Argon TPCs; a case study with the MicroBooNE detector

Cosmic ray (CR) interactions can be a challenging source of background for neutrino oscillation and cross-section measurements in surface detectors. We present methods for CR rejection in measurements of charged-current quasielastic-like (CCQE-like) neutrino interactions, with a muon and a proton in the final state, measured using liquid argon time projection chambers (LArTPCs). Using a sample of cosmic data collected with the MicroBooNE detector, mixed with simulated neutrino scattering events, a set of event selection criteria is developed that produces an event sample with minimal contribution from CR background. Depending on the selection criteria used a purity between 50% and 80% can be achieved with a signal selection efficiency between 50% and 25%, with higher purity coming at the expense of lower efficiency. While using a specific dataset from the MicroBooNE detector and selection criteria values optimized for CCQE-like events, the concepts presented here are generic and can be adapted for various studies of exclusive {\nu}{\mu} interactions in LArTPCs.Comment: 12 pages, 10 figures, 1 tabl