Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Study and optimization of the spatial resolution for detectors with binary readout

Using simulations and analytical approaches, we have studied single hit resolutions obtained with a binary readout, which is often proposed for high granularity detectors to reduce the generated data volume. Our simulations considering several parameters (e.g. strip pitch) show that the detector geometry and an electronics parameter of the binary readout chips could be optimized for binary readout to offer an equivalent spatial resolution to the one with an analogue readout. To understand the behavior as a function of simulation parameters, we developed analytical models that reproduce simulation results with a few parameters. The models can be used to optimize detector designs and operation conditions with regard to the spatial resolution.Comment: 21 pages, 20 figure

Particle identification

Particle IDentification (PID) is fundamental to particle physics experiments. This paper reviews PID strategies and methods used by the large LHC experiments, which provide outstanding examples of the state-of-the-art. The first part focuses on the general design of these experiments with respect to PID and the technologies used. Three PID techniques are discussed in more detail: ionization measurements, time-of-flight measurements and Cherenkov imaging. Four examples of the implementation of these techniques at the LHC are given, together with selections of relevant examples from other experiments and short overviews on new developments. Finally, the Alpha Magnetic Spectrometer (AMS 02) experiment is briefly described as an impressive example of a space-based experiment using a number of familiar PID techniques.Comment: 61 pages, 30 figure

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

The Highly Miniaturised Radiation Monitor

We present the design and preliminary calibration results of a novel highly miniaturised particle radiation monitor (HMRM) for spacecraft use. The HMRM device comprises a telescopic configuration of active pixel sensors enclosed in a titanium shield, with an estimated total mass of 52 g and volume of 15 cm$^3$. The monitor is intended to provide real-time dosimetry and identification of energetic charged particles in fluxes of up to 10$^8$ cm$^{-2}$ s$^{-1}$ (omnidirectional). Achieving this capability with such a small instrument could open new prospects for radiation detection in space.Comment: 17 pages, 15 figure