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9 results on '"Yates, Lauren Elizabeth"'

1. Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

Author

Massachusetts Institute of Technology. Department of Physics, Ashkenazi, Adi, Carr, Rachel, Conrad, Janet M., Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Jarrett S., Papadopoulou, Afroditi, Yates, Lauren Elizabeth, Massachusetts Institute of Technology. Department of Physics, Ashkenazi, Adi, Carr, Rachel, Conrad, Janet M., Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Jarrett S., Papadopoulou, Afroditi, and Yates, Lauren Elizabeth

Abstract

© 2020 IOP Publishing Ltd and Sissa Medialab. We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration.

Published
2022

2. Design and construction of the MicroBooNE Cosmic Ray Tagger system

Author

Massachusetts Institute of Technology. Department of Nuclear Science and Engineering, Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Laboratory for Nuclear Science, MicroBooNE Collaboration, Ashkenazi, Adi, Carr, Rachel, Collin, G. H., Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Joongho, Papadopoulou, Afroditi, Yates, Lauren Elizabeth, Massachusetts Institute of Technology. Department of Nuclear Science and Engineering, Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Laboratory for Nuclear Science, MicroBooNE Collaboration, Ashkenazi, Adi, Carr, Rachel, Collin, G. H., Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Joongho, Papadopoulou, Afroditi, and Yates, Lauren Elizabeth

Abstract

© 2019 IOP Publishing Ltd and Sissa Medialab. 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.

Published
2022

3. A method to determine the electric field of liquid argon time projection chambers using a UV laser system and its application in MicroBooNE

Author

Massachusetts Institute of Technology. Laboratory for Nuclear Science, Massachusetts Institute of Technology. Department of Nuclear Science and Engineering, Ashkenazi, Adi, Carr, Rachel, Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Joongho, Papadopoulou, Afroditi, Yates, Lauren Elizabeth, Massachusetts Institute of Technology. Laboratory for Nuclear Science, Massachusetts Institute of Technology. Department of Nuclear Science and Engineering, Ashkenazi, Adi, Carr, Rachel, Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Joongho, Papadopoulou, Afroditi, and Yates, Lauren Elizabeth

Abstract

© 2020 The Author(s). Liquid argon time projection chambers (LArTPCs) are now a standard detector technology for making accelerator neutrino measurements, due to their high material density, precise tracking, and calorimetric capabilities. An electric field (E-field) is required in such detectors to drift ionization electrons to the anode where they are collected. The E-field of a TPC is often approximated to be uniform between the anode and the cathode planes. However, significant distortions can appear from effects such as mechanical deformations, electrode failures, or the accumulation of space charge generated by cosmic rays. The latter effect is particularly relevant for detectors placed near the Earth's surface and with large drift distances and long drift time. To determine the E-field in situ, an ultraviolet (UV) laser system is installed in the MicroBooNE experiment at Fermi National Accelerator Laboratory. The purpose of this system is to provide precise measurements of the E-field, and to make it possible to correct for 3D spatial distortions due to E-field non-uniformities. Here we describe the methodology developed for deriving spatial distortions, the drift velocity and the E-field from UV-laser measurements.

Published
2022

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

Author

Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies, Collin, G. H., Conrad, Janet Marie, Hen, Or, Moon, Joongho, Wongjirad, Taritree, Yates, Lauren Elizabeth, Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies, Collin, G. H., Conrad, Janet Marie, Hen, Or, Moon, Joongho, Wongjirad, Taritree, and Yates, Lauren Elizabeth

Abstract

© 2017 IOP Publishing Ltd and Sissa Medialab. 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.

Published
2022

5. Ionization electron signal processing in single phase LArTPCs. Part I. Algorithm Description and quantitative evaluation with MicroBooNE simulation

Author

Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Laboratory for Nuclear Science, Collin, G. H., Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Jarrett S., Papadopoulou, Afroditi, Yates, Lauren Elizabeth, Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Laboratory for Nuclear Science, Collin, G. H., Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Jarrett S., Papadopoulou, Afroditi, and Yates, Lauren Elizabeth

Abstract

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. Keywords: MicroBooNE, Signal Processing, Deconvolution, ROI, United States. Department of Energy. High Energy Physics Division, National Science Foundation (U.S.), Swiss National Science Foundation, Science and Technology Facilities Council (Great Britain), Royal Society (Great Britain)

Published
2019

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

Author

Collin, G. H., Conrad, Janet Marie, Hen, Or, Hourlier, Adrien C., Moon, J., Wongjirad, Taritree, Yates, Lauren Elizabeth, Acciarri, R., Adams, C., An, R., Anthony, J., Asaadi, J., Auger, M., Bagby, L., Balasubramanian, S., Baller, B., Barnes, C., Barr, G., Bass, M., Bay, F., Bishai, M., Blake, A., Bolton, T., Camilleri, L., Caratelli, D., Carls, B., Castillo Fernandez, R., Cavanna, F., Chen, H., Church, E., Cianci, D., Cohen, E., Convery, M., Crespo-Anadón, J. I, Del Tutto, M., Devitt, D., Dytman, S., Eberly, B., Ereditato, A., Escudero Sanchez, L., Esquivel, J., Fadeeva, A. A, Fleming, B. T, Foreman, W., Furmanski, A. P, Garcia-Gamez, D., Garvey, G. T, Genty, V., Goeldi, D., Gollapinni, S., Graf, N., Gramellini, E., Greenlee, H., Grosso, R., Guenette, R., Hackenburg, A., Hamilton, P., Hewes, J., Hill, C., Ho, J., Horton-Smith, G., Huang, E.-C., James, C., Jan de Vries, J., Jen, C.-M., Jiang, L., Johnson, R. A, Joshi, J., Jostlein, H., Kaleko, D., Karagiorgi, G., Ketchum, W., Kirby, B., Kirby, M., Kobilarcik, T., Kreslo, I., Laube, A., Li, Y., Lister, A., Littlejohn, B. R, Lockwitz, S., Lorca, D., Louis, W. C, Luethi, M., Lundberg, B., Luo, X., Marchionni, A., Mariani, C., Marshall, J., Martinez Caicedo, D. A, Meddage, V., Miceli, T., Mills, G. B, Mooney, M., Moore, C. D, Mousseau, J., Murrells, R., Naples, D., Nienaber, P., Nowak, J., Palamara, O., Paolone, V., Papavassiliou, V., Pate, S. F, Pavlovic, Z., Piasetzky, E., Porzio, D., Pulliam, G., Qian, X., Raaf, J. L, Rafique, A., Rochester, L., Rudolf von Rohr, C., Russell, B., Schmitz, D. W, Schukraft, A., Seligman, W., Shaevitz, M. H, Sinclair, J., Smith, A., Snider, E. L, Soderberg, M., Söldner-Rembold, S., Soleti, S. R, Spentzouris, P., Spitz, J., St. John, J., Strauss, T., Szelc, A. M, Tagg, N., Terao, K., Thomson, M., Toups, M., Tsai, Y.-T., Tufanli, S., Usher, T., Van De Pontseele, W., Van de Water, R. G, Viren, B., Weber, M., Wickremasinghe, D. A, Wolbers, S., Woodruff, K., Yang, T., Zeller, G. P, Zennamo, J., Zhang, C., Collin, G. H., Conrad, Janet Marie, Hen, Or, Hourlier, Adrien C., Moon, J., Wongjirad, Taritree, Yates, Lauren Elizabeth, Acciarri, R., Adams, C., An, R., Anthony, J., Asaadi, J., Auger, M., Bagby, L., Balasubramanian, S., Baller, B., Barnes, C., Barr, G., Bass, M., Bay, F., Bishai, M., Blake, A., Bolton, T., Camilleri, L., Caratelli, D., Carls, B., Castillo Fernandez, R., Cavanna, F., Chen, H., Church, E., Cianci, D., Cohen, E., Convery, M., Crespo-Anadón, J. I, Del Tutto, M., Devitt, D., Dytman, S., Eberly, B., Ereditato, A., Escudero Sanchez, L., Esquivel, J., Fadeeva, A. A, Fleming, B. T, Foreman, W., Furmanski, A. P, Garcia-Gamez, D., Garvey, G. T, Genty, V., Goeldi, D., Gollapinni, S., Graf, N., Gramellini, E., Greenlee, H., Grosso, R., Guenette, R., Hackenburg, A., Hamilton, P., Hewes, J., Hill, C., Ho, J., Horton-Smith, G., Huang, E.-C., James, C., Jan de Vries, J., Jen, C.-M., Jiang, L., Johnson, R. A, Joshi, J., Jostlein, H., Kaleko, D., Karagiorgi, G., Ketchum, W., Kirby, B., Kirby, M., Kobilarcik, T., Kreslo, I., Laube, A., Li, Y., Lister, A., Littlejohn, B. R, Lockwitz, S., Lorca, D., Louis, W. C, Luethi, M., Lundberg, B., Luo, X., Marchionni, A., Mariani, C., Marshall, J., Martinez Caicedo, D. A, Meddage, V., Miceli, T., Mills, G. B, Mooney, M., Moore, C. D, Mousseau, J., Murrells, R., Naples, D., Nienaber, P., Nowak, J., Palamara, O., Paolone, V., Papavassiliou, V., Pate, S. F, Pavlovic, Z., Piasetzky, E., Porzio, D., Pulliam, G., Qian, X., Raaf, J. L, Rafique, A., Rochester, L., Rudolf von Rohr, C., Russell, B., Schmitz, D. W, Schukraft, A., Seligman, W., Shaevitz, M. H, Sinclair, J., Smith, A., Snider, E. L, Soderberg, M., Söldner-Rembold, S., Soleti, S. R, Spentzouris, P., Spitz, J., St. John, J., Strauss, T., Szelc, A. M, Tagg, N., Terao, K., Thomson, M., Toups, M., Tsai, Y.-T., Tufanli, S., Usher, T., Van De Pontseele, W., Van de Water, R. G, Viren, B., Weber, M., Wickremasinghe, D. A, Wolbers, S., Woodruff, K., Yang, T., Zeller, G. P, Zennamo, J., and Zhang, C.

Abstract

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.

Published
2018

7. Michel electron reconstruction using cosmic-ray data from the MicroBooNE LArTPC

Author

MicroBooNE Collaboration, Acciarri, R., Adams, C., An, R., Anthony, J., Asaadi, J., Auger, M., Bagby, L., Balasubramanian, S., Baller, B., Barnes, C., Barr, G., Bass, M., Bay, F., Bishai, M., Blake, A., Bolton, T., Bugel, L., Camilleri, L., Caratelli, D., Carls, B., Fernandez, R. Castillo, Cavanna, F., Chen, H., Church, E., Cianci, D., Cohen, E., Collin, G. H., Conrad, J. M., Convery, M., Crespo-Anadon, J. I., Del Tutto, M., Devitt, D., Dytman, S., Eberly, B., Ereditato, A., Sanchez, L. Escudero, Esquivel, J., Fleming, B. T., Foreman, W., Furmanski, A. P., Garcia-Gamez, D., Garvey, G. T., Genty, V., Goeldi, D., Gollapinni, S., Graf, N., Gramellini, E., Greenlee, H., Grosso, R., Guenette, R., Hackenburg, A., Hamilton, P., Hen, O., Hewes, V, Hill, C., Ho, J., Horton-Smith, G., Huang, E. -C., James, C., de Vries, J. Jan, Jen, C. -M., Jiang, L., Johnson, R. A., Joshi, J., Jostlein, H., Kaleko, D., Karagiorgi, G., Ketchum, W., Kirby, B., Kirby, M., Kobilarcik, T., Kreslo, I., Laube, A., Li, Y., Lister, A., Littlejohn, B. R., Lockwitz, S., Lorca, D., Louis, W. C., Luethi, M., Lundberg, B., Luo, X., Marchionni, A., Mariani, C., Marshall, J., Caicedo, D. A. Martinez, Meddage, V., Miceli, T., Mills, G. B., Moon, J., Mooney, M., Moore, C. D., Mousseau, J., Murrells, R., Naples, D., Nienaber, P., Nowak, J., Palamara, O., Paolone, V., Papavassiliou, V., Pate, S. F., Pavlovic, Z., Piasetzky, E., Porzio, D., Pulliam, G., Qian, X., Raaf, J. L., Rafique, A., Rochester, L., von Rohr, C. Rudolf, Russell, B., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sinclair, J., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Soleti, S. R., Spentzouris, P., Spitz, J., John, J. St., Strauss, T., Sutton, K. A., Szelc, A. M., Tagg, N., Terao, K., Thomson, M., Toups, M., Tsai, Y. -T., Tufanli, S., Usher, T., Van de Water, R. G., Viren, B., Weber, M., Wickremasinghe, D. A., Wolbers, S., Wongjirad, T., Woodruff, K., Yang, T., Yates, L., Zeller, G. P., Zennamo, J., Zhang, C., Moon, Jarrett S., Conrad, Janet Marie, Hen, Or, and Yates, Lauren Elizabeth

Subjects
Physics - Instrumentation and Detectors, Physics::Instrumentation and Detectors, Time projection chambers, FOS: Physical sciences, Cosmic ray, Electron, Neutrino detectors, Noble liquid detectors (scintillation, ionization, double-phase), Performance of High Energy Physics Detectors, 01 natural sciences, High Energy Physics - Experiment, Nuclear physics, High Energy Physics - Experiment (hep-ex), Noble liquid detectors (scintillation, Ionization, ionization, 0103 physical sciences, Fermilab, 010306 general physics, Instrumentation, Mathematical Physics, Physics, Range (particle radiation), Time projection chamber, Muon, 010308 nuclear & particles physics, Instrumentation and Detectors (physics.ins-det), double-phase), High Energy Physics::Experiment, Neutrino
Abstract

The MicroBooNE liquid argon time projection chamber (LArTPC) has been taking data at Fermilab since 2015 collecting, in addition to neutrino beam, cosmic-ray muons. Results are presented on the reconstruction of Michel electrons produced by the decay at rest of cosmic-ray muons. Michel electrons are abundantly produced in the TPC, and given their well known energy spectrum can be used to study MicroBooNE's detector response to low-energy electrons (electrons with energies up to ∼ 50 MeV). We describe the fully-automated algorithm developed to reconstruct Michel electrons, with which a sample of ∼ 14,000 Michel electron candidates is obtained. Most of this article is dedicated to studying the impact of radiative photons produced by Michel electrons on the accuracy and resolution of their energy measurement. In this energy range, ionization and bremsstrahlung photon production contribute similarly to electron energy loss in argon, leading to a complex electron topology in the TPC. By profiling the performance of the reconstruction algorithm on simulation we show that the ability to identify and include energy deposited by radiative photons leads to a significant improvement in the energy measurement of low-energy electrons. The fractional energy resolution we measure improves from over 30% to ∼ 20% when we attempt to include radiative photons in the reconstruction. These studies are relevant to a large number of analyses which aim to study neutrinos by measuring electrons produced by ν e interactions over a broad energy range. Keywords: Michel electrons, LArTPC, MicroBooNE

Published
2018

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

Author

W. Foreman, V. Paolone, A. Hourlier, T. Kobilarcik, Colin Hill, H. S. Chen, Bo Yu, C. Zhang, D.A. Wickremasinghe, L.E. Yates, J. Ho, L. Bagby, T. Miceli, A. P. Furmanski, S. Marcocci, T. Yang, K. Bhattacharya, R. Grosso, J. Sinclair, J. I. Crespo-Anadón, T. Wongjirad, M. Soderberg, R. G. Van de Water, C.D. Moore, J. Jan de Vries, Vishvas Pandey, Afroditi Papadopoulou, W. Ketchum, B.T. Fleming, D. W. Schmitz, S. Dytman, D. Cianci, A. Bhat, L. Camilleri, J. L. Raaf, D. Kaleko, Veljko Radeka, D. Devitt, W. Tang, E.-C. Huang, J. A. Nowak, Or Hen, G. B. Mills, M. Del Tutto, V. Genty, Z. Williams, R. Guenette, K. Wierman, A.A. Fadeeva, L. Rochester, Marc Weber, A. Marchionni, S. Balasubramanian, A. Lister, B. Eberly, Andrew Blake, L. Jiang, Antonio Ereditato, J. Esquivel, J. Anthony, R. Murrells, M. H. Shaevitz, F. Cavanna, Michael T. Murphy, M. Bishai, A. Diaz, Panagiotis Spentzouris, C. Barnes, P. M. Hamilton, E. Cohen, A. Rafique, F. Bay, J. Moon, C. Rudolf von Rohr, H. Y. Wei, Michael H Kirby, Y.-J. Jwa, G. Karagiorgi, P. Nienaber, L. Escudero Sanchez, A. Mastbaum, B. Lundberg, D. Naples, S.R. Soleti, B. Viren, K. Woodruff, R. Castillo Fernandez, A. M. Szelc, C. Mariani, T. Usher, D. Lorca, E. Gramellini, Ornella Palamara, R. A. Johnson, J. Mousseau, W. C. Louis, S. Sword-Fehlberg, Andrew Smith, Z. Pavlovic, H. Greenlee, Giuseppe Benedetto Cerati, K. Sutton, B. Kirby, C. Adams, M. Bass, E. Church, Y.-T. Tsai, I. Kreslo, P. Guzowski, Thomas Strauss, C. E. Thorn, V. Meddage, A. Schukraft, N. Tagg, D. A. Martinez Caicedo, G.D. Barr, L. Cooper-Troendle, T. Bolton, Yang Li, X. Luo, W. Van De Pontseele, M. Ross-Lonergan, D. Caratelli, J. St. John, M. Luethi, A. Hackenburg, M. A. Thomson, Kazuhiro Terao, E. Piasetzky, G. Yarbrough, G. Pulliam, J. J. Evans, S. Wolbers, Yi Chen, Xin Qian, R. An, G. H. Collin, G. A. Horton-Smith, B. R. Littlejohn, J. Asaadi, D. Garcia-Gamez, S. F. Pate, Janet Conrad, C. James, V. Papavassiliou, M. Mooney, Martin Auger, J. Spitz, B. Russell, S. Lockwitz, W. G. Seligman, M. E. Convery, G. T. Garvey, H. Jostlein, D. Goeldi, J. Zennamo, S. Gollapinni, M. Toups, E.L. Snider, G. P. Zeller, John Marshall, D. Porzio, S. Tufanli, S. Söldner-Rembold, J. Joshi, J. Hewes, A. Mogan, B. Baller, Massachusetts Institute of Technology. Department of Physics, Massachusetts Institute of Technology. Laboratory for Nuclear Science, Collin, G. H., Conrad, Janet Marie, Diaz, Alejandro, Hen, Or, Hourlier, Adrien C., Moon, Jarrett S., Papadopoulou, Afroditi, and Yates, Lauren Elizabeth

Subjects
Physics - Instrumentation and Detectors, Physics::Instrumentation and Detectors, Time projection chambers, FOS: Physical sciences, Electron, 01 natural sciences, High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), Ionization, 0103 physical sciences, Waveform, Neutrino detectors, Nuclear Experiment (nucl-ex), 010306 general physics, Instrumentation, Nuclear Experiment, Mathematical Physics, Physics, Signal processing, Time projection chamber, Tomographic reconstruction, 010308 nuclear & particles physics, Detector, Instrumentation and Detectors (physics.ins-det), Data processing methods, Deconvolution, Algorithm
Abstract

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. Keywords: MicroBooNE, Signal Processing, Deconvolution, ROI, United States. Department of Energy. High Energy Physics Division, National Science Foundation (U.S.), Swiss National Science Foundation, Science and Technology Facilities Council (Great Britain), Royal Society (Great Britain)

Published
2018

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

Author

D. Cianci, A. P. Furmanski, B. Russell, R. Acciarri, W. G. Seligman, B. Eberly, J. Anthony, J. L. Raaf, H. S. Chen, D. Goeldi, C. Adams, D. Kaleko, J. Zennamo, A. Hourlier, M. Auger, D. Garcia-Gamez, S. F. Pate, C. James, T. Kobilarcik, B. R. Littlejohn, V. Papavassiliou, G. H. Collin, M. Mooney, J. Joshi, D. A. Martinez Caicedo, J. Asaadi, C. Zhang, D. Lorca, W. Ketchum, R. Guenette, F. Bay, T. Miceli, T. Usher, R. G. Van de Water, Michael H Kirby, R. Grosso, G. A. Horton-Smith, B. Baller, L. Bagby, C. Barnes, A. Rafique, B. Lundberg, E. Gramellini, M. Bishai, E. Cohen, J. A. Nowak, F. Cavanna, G. T. Garvey, Z. Pavlovic, Y.-T. Tsai, E.-C. Huang, P. M. Hamilton, G. Karagiorgi, M. Luethi, P. Nienaber, Janet Conrad, J. Esquivel, Panagiotis Spentzouris, G. P. Zeller, T. Wongjirad, J. St. John, Xin Qian, R. Castillo Fernandez, K. Woodruff, X. Luo, John Marshall, A. M. Szelc, Ornella Palamara, R. A. Johnson, J. Moon, Colin Hill, A. Marchionni, D. Naples, J. Ho, G. B. Mills, A. Schukraft, E.L. Snider, W. C. Louis, H. Jöstlein, S. Gollapinni, D. Porzio, C. Mariani, H. Greenlee, C.-M. Jen, Luke A. Yates, Thomas Strauss, M. A. Thomson, J. Sinclair, J. I. Crespo-Anadón, R. An, J. Hewes, T. Yang, S. Tufanli, W. Foreman, V. Paolone, Kazuhiro Terao, B. Kirby, E. Piasetzky, B.T. Fleming, S. Dytman, T. Bolton, S. Söldner-Rembold, N. Graf, D. W. Schmitz, J. Jan de Vries, D. Devitt, M. Soderberg, B. Carls, V. Genty, Andrew Blake, L. Jiang, A. Laube, G. Pulliam, M. H. Shaevitz, L. Camilleri, M. Toups, J. Spitz, Or Hen, Marc Weber, M. E. Convery, Andrew Smith, I. Kreslo, S.R. Soleti, B. Viren, J. Mousseau, M. Del Tutto, C. Rudolf von Rohr, Antonio Ereditato, L. Escudero Sanchez, M. Bass, E. Church, N. Tagg, G.D. Barr, D. Caratelli, A. Hackenburg, Yang Li, W. Van De Pontseele, C.D. Moore, S. Lockwitz, S. Balasubramanian, A. Lister, S. Wolbers, V. Meddage, D.A. Wickremasinghe, L. Rochester, A.A. Fadeeva, R. Murrells, Collin, G. H., Conrad, Janet Marie, Hen, Or, Hourlier, Adrien C., Moon, J., Wongjirad, Taritree, and Yates, Lauren Elizabeth

Subjects
Physics and Astronomy (miscellaneous), Exploit, Regular Article - Experimental Physics, lcsh:Astrophysics, computer.software_genre, Network topology, 01 natural sciences, Task (project management), lcsh:QB460-466, 0103 physical sciences, lcsh:Nuclear and particle physics. Atomic energy. Radioactivity, Detectors and Experimental Techniques, 010306 general physics, Engineering (miscellaneous), QC, Physics, 010308 nuclear & particles physics, business.industry, Event (computing), Detector, Software development, Pattern recognition, Advanced software [3], Pattern recognition (psychology), lcsh:QC770-798, Data mining, Artificial intelligence, Neutrino, business, computer, Algorithm
Abstract

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.

Published
2018

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