An Assessment of Group Size in Interteaching

A key component of interteaching, as described by Boyce and Hineline (2002), is the opportunity for students to participate in "dyadic" or pair discussions. Although the rationale for pair discussions is evident, only one study to date has evaluated the relative effectiveness of student performance when group size is manipulated. The present investigation was designed to further evaluate the effect of group size during pair discussions on student quiz scores in an introductory psychology course with a diverse group of learners. An alternating treatments design was implemented whereby students were assigned to work in a dyad or in groups of 4-5 students to discuss a preparation guide. All of the major components of interteaching were in effect during both conditions (i.e., availability of prep guides and quality points, clarifying lectures, and frequent test probes). Results showed a small advantage for performance following discussion in dyads, although a social validity measure indicated students favored discussion in larger groups. Implications of these findings and suggestions for future work will be discussed.

Enhancing the impact of quality points in interteaching

In prior analysis of interteaching with a quality points contingency no significant difference was reported in student exam scores when quality points were made available. In the present study, we employed an alternating treatments design to compare student performance on post-discussion quizzes when a quality points contingency was alternated across class sessions and feedback on quiz performance was provided immediately following the submission of each quiz. Results indicate average quiz performance was slightly higher following class sessions with the quality points contingency.

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation, we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Measurement of cosmic-ray reconstruction efficiencies in the MicroBooNE LArTPC using a small external cosmic-ray counter

The MicroBooNE detector is a liquid argon time projection chamber at Fermilab designed to study short-baseline neutrino oscillations and neutrino-argon interaction cross-section. Due to its location near the surface, a good understanding of cosmic muons as a source of backgrounds is of fundamental importance for the experiment. We present a method of using an external 0.5 m (L) x 0.5 m (W) muon counter stack, installed above the main detector, to determine the cosmic-ray reconstruction efficiency in MicroBooNE. Data are acquired with this external muon counter stack placed in three different positions, corresponding to cosmic rays intersecting different parts of the detector. The data reconstruction efficiency of tracks in the detector is found to be $\epsilon_{\mathrm{data}}=(97.1\pm0.1~(\mathrm{stat}) \pm 1.4~(\mathrm{sys}))\%$, in good agreement with the Monte Carlo reconstruction efficiency $\epsilon_{\mathrm{MC}} = (97.4\pm0.1)\%$. This analysis represents a small-scale demonstration of the method that can be used with future data coming from a recently installed cosmic-ray tagger system, which will be able to tag $\approx80\%$ of the cosmic rays passing through the MicroBooNE detector.Comment: 19 pages, 12 figure

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure

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

Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE

The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of induction plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.Comment: 54 pages, 36 figures; the first part of this work can be found at arXiv:1802.0870

Ionization Electron Signal Processing in Single Phase LArTPCs I. Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation

We describe the concept and procedure of drifted-charge extraction developed in the MicroBooNE experiment, a single-phase liquid argon time projection chamber (LArTPC). This technique converts the raw digitized TPC waveform to the number of ionization electrons passing through a wire plane at a given time. A robust recovery of the number of ionization electrons from both induction and collection anode wire planes will augment the 3D reconstruction, and is particularly important for tomographic reconstruction algorithms. A number of building blocks of the overall procedure are described. The performance of the signal processing is quantitatively evaluated by comparing extracted charge with the true charge through a detailed TPC detector simulation taking into account position-dependent induced current inside a single wire region and across multiple wires. Some areas for further improvement of the performance of the charge extraction procedure are also discussed.Comment: 60 pages, 36 figures. The second part of this work can be found at arXiv:1804.0258

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