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6 results on '"Luethi, M."'

1. Search for heavy neutral leptons decaying into muon-pion pairs in the MicroBooNE detector

Author

Abratenko, P, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Basque, V, Berkman, S, Bhanderi, A, Bhat, A, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Terrazas, I Caro, Fernandez, R Castillo, Cavanna, F, Cerati, G, Chen, Y, Church, E, Cianci, D, Cohen, EO, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadón, JI, Del Tutto, M, Devitt, A, Domine, L, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Sanchez, L Escudero, Evans, JJ, Fitzpatrick, RS, Fleming, BT, Foppiani, N, Franco, D, Furmanski, AP, Garcia-Gamez, D, Gardiner, S, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Green, P, Greenlee, H, Gu, L, Gu, W, Guenette, R, Guzowski, P, Hamilton, P, Hen, O, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, E-C, Itay, R, James, C, de Vries, J Jan, Ji, X, Jiang, L, Jo, JH, Johnson, RA, Joshi, J, Jwa, Y-J, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, LaZur, R, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Caicedo, DA Martinez, Mason, K, Mastbaum, A, McConkey, N, and Meddage, V

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences, hep-ex, physics.ins-det, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Mathematical physics, Astronomical sciences, Particle and high energy physics
Abstract

We present upper limits on the production of heavy neutral leptons (HNLs) decaying to μπ pairs using data collected with the MicroBooNE liquid-argon time projection chamber (TPC) operating at Fermilab. This search is the first of its kind performed in a liquid-argon TPC. We use data collected in 2017 and 2018 corresponding to an exposure of 2.0×1020 protons on target from the Fermilab Booster Neutrino Beam, which produces mainly muon neutrinos with an average energy of ≈800 MeV. HNLs with higher mass are expected to have a longer time of flight to the liquid-argon TPC than Standard Model neutrinos. The data are therefore recorded with a dedicated trigger configured to detect HNL decays that occur after the neutrino spill reaches the detector. We set upper limits at the 90% confidence level on the element |Uμ4|2 of the extended PMNS mixing matrix in the range |Uμ4|2

Published
2020

2. Search for heavy neutral leptons decaying into muon-pion pairs in the MicroBooNE detector

Author

Abratenko, P, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Basque, V, Berkman, S, Bhanderi, A, Bhat, A, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Caro Terrazas, I, Castillo Fernandez, R, Cavanna, F, Cerati, G, Chen, Y, Church, E, Cianci, D, Cohen, EO, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadón, JI, Del Tutto, M, Devitt, D, Domine, L, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Escudero Sanchez, L, Evans, JJ, Fitzpatrick, RS, Fleming, BT, Foppiani, N, Franco, D, Furmanski, AP, Garcia-Gamez, D, Gardiner, S, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Green, P, Greenlee, H, Gu, L, Gu, W, Guenette, R, Guzowski, P, Hamilton, P, Hen, O, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, EC, Itay, R, James, C, Jan De Vries, J, Ji, X, Jiang, L, Jo, JH, Johnson, RA, Joshi, J, Jwa, YJ, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Lazur, R, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Martinez Caicedo, DA, Mason, K, Mastbaum, A, McConkey, N, and Meddage, V

Subjects
hep-ex, physics.ins-det
Abstract

We present upper limits on the production of heavy neutral leptons (HNLs) decaying to μπ pairs using data collected with the MicroBooNE liquid-argon time projection chamber (TPC) operating at Fermilab. This search is the first of its kind performed in a liquid-argon TPC. We use data collected in 2017 and 2018 corresponding to an exposure of 2.0×1020 protons on target from the Fermilab Booster Neutrino Beam, which produces mainly muon neutrinos with an average energy of ≈800 MeV. HNLs with higher mass are expected to have a longer time of flight to the liquid-argon TPC than Standard Model neutrinos. The data are therefore recorded with a dedicated trigger configured to detect HNL decays that occur after the neutrino spill reaches the detector. We set upper limits at the 90% confidence level on the element |Uμ4|2 of the extended PMNS mixing matrix in the range |Uμ4|2

Published
2020

3. Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber

Author

Adams, C, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Auger, M, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Bass, M, Bay, F, Bhat, A, Bhattacharya, K, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Terrazas, I Caro, Carr, R, Fernandez, R Castillo, Cavanna, F, Cerati, G, Chen, Y, Church, E, Cianci, D, Cohen, EO, Collin, GH, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadón, JI, Del Tutto, M, Devitt, A, Diaz, A, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Sanchez, L Escudero, Esquivel, J, Evans, JJ, Fadeeva, AA, Fitzpatrick, RS, Fleming, BT, Franco, D, Furmanski, AP, Garcia-Gamez, D, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Greenlee, H, Grosso, R, Guenette, R, Guzowski, P, Hackenburg, A, Hamilton, P, Hen, O, Hewes, J, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, E-C, James, C, de Vries, J Jan, Ji, X, Jiang, L, Johnson, RA, Joshi, J, Jostlein, H, Jwa, Y-J, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Caicedo, DA Martinez, Mastbaum, A, Meddage, V, and Mettler, T

Subjects
Nuclear and Plasma Physics, Physical Sciences, Neurosciences, hep-ex, cs.CV, physics.data-an, physics.ins-det, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Mathematical physics, Astronomical sciences, Particle and high energy physics
Abstract

We have developed a convolutional neural network 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 νμ charged-current neutral pion data samples.

Published
2019

4. First measurement of νμ charged-current π0 production on argon with the MicroBooNE detector

Author

Adams, C, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Auger, M, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Bass, M, Bay, F, Bhat, A, Bhattacharya, K, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Terrazas, I Caro, Carr, R, Fernandez, R Castillo, Cavanna, F, Cerati, G, Chen, H, Chen, Y, Church, E, Cianci, D, Cohen, E, Collin, GH, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadón, JI, Del Tutto, M, Devitt, A, Diaz, A, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Sanchez, L Escudero, Esquivel, J, Evans, JJ, Fadeeva, AA, Fitzpatrick, RS, Fleming, BT, Franco, D, Furmanski, AP, Garcia-Gamez, D, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Greenlee, H, Grosso, R, Guenette, R, Guzowski, P, Hackenburg, A, Hamilton, P, Hen, O, Hewes, J, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, E-C, James, C, de Vries, J Jan, Ji, X, Jiang, L, Johnson, RA, Joshi, J, Jostlein, H, Jwa, Y-J, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Caicedo, DA Martinez, Mastbaum, A, and Meddage, V

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Synchrotrons and Accelerators, Physical Sciences, hep-ex, physics.ins-det, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Mathematical physics, Astronomical sciences, Particle and high energy physics
Abstract

We report the first measurement of the flux-integrated cross section of νμ charged-current single π0 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.

Published
2019

5. Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber

Author

Adams, C, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Auger, M, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Bass, M, Bay, F, Bhat, A, Bhattacharya, K, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Caro Terrazas, I, Carr, R, Castillo Fernandez, R, Cavanna, F, Cerati, G, Chen, Y, Church, E, Cianci, D, Cohen, EO, Collin, GH, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadón, JI, Del Tutto, M, Devitt, D, Diaz, A, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Escudero Sanchez, L, Esquivel, J, Evans, JJ, Fadeeva, AA, Fitzpatrick, RS, Fleming, BT, Franco, D, Furmanski, AP, Garcia-Gamez, D, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Greenlee, H, Grosso, R, Guenette, R, Guzowski, P, Hackenburg, A, Hamilton, P, Hen, O, Hewes, J, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, EC, James, C, Jan De Vries, J, Ji, X, Jiang, L, Johnson, RA, Joshi, J, Jostlein, H, Jwa, YJ, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Martinez Caicedo, DA, Mastbaum, A, Meddage, V, and Mettler, T

Subjects
hep-ex, cs.CV, physics.data-an, physics.ins-det
Abstract

We have developed a convolutional neural network 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 νμ charged-current neutral pion data samples.

Published
2019

6. First measurement of νμ charged-current π0 production on argon with the MicroBooNE detector

Author

Adams, C, Alrashed, M, An, R, Anthony, J, Asaadi, J, Ashkenazi, A, Auger, M, Balasubramanian, S, Baller, B, Barnes, C, Barr, G, Bass, M, Bay, F, Bhat, A, Bhattacharya, K, Bishai, M, Blake, A, Bolton, T, Camilleri, L, Caratelli, D, Caro Terrazas, I, Carr, R, Castillo Fernandez, R, Cavanna, F, Cerati, G, Chen, H, Chen, Y, Church, E, Cianci, D, Cohen, E, Collin, GH, Conrad, JM, Convery, M, Cooper-Troendle, L, Crespo-Anadón, JI, Del Tutto, M, Devitt, D, Diaz, A, Duffy, K, Dytman, S, Eberly, B, Ereditato, A, Escudero Sanchez, L, Esquivel, J, Evans, JJ, Fadeeva, AA, Fitzpatrick, RS, Fleming, BT, Franco, D, Furmanski, AP, Garcia-Gamez, D, Genty, V, Goeldi, D, Gollapinni, S, Goodwin, O, Gramellini, E, Greenlee, H, Grosso, R, Guenette, R, Guzowski, P, Hackenburg, A, Hamilton, P, Hen, O, Hewes, J, Hill, C, Horton-Smith, GA, Hourlier, A, Huang, EC, James, C, Jan De Vries, J, Ji, X, Jiang, L, Johnson, RA, Joshi, J, Jostlein, H, Jwa, YJ, Karagiorgi, G, Ketchum, W, Kirby, B, Kirby, M, Kobilarcik, T, Kreslo, I, Lepetic, I, Li, Y, Lister, A, Littlejohn, BR, Lockwitz, S, Lorca, D, Louis, WC, Luethi, M, Lundberg, B, Luo, X, Marchionni, A, Marcocci, S, Mariani, C, Marshall, J, Martin-Albo, J, Martinez Caicedo, DA, Mastbaum, A, and Meddage, V

Subjects
hep-ex, physics.ins-det
Abstract

We report the first measurement of the flux-integrated cross section of νμ charged-current single π0 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.

Published
2019

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