Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 72 tok/s
Gemini 2.5 Pro 45 tok/s Pro
GPT-5 Medium 33 tok/s Pro
GPT-5 High 29 tok/s Pro
GPT-4o 93 tok/s Pro
Kimi K2 211 tok/s Pro
GPT OSS 120B 442 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Demonstration of new MeV-scale capabilities in large neutrino LArTPCs using ambient radiogenic and cosmogenic activity in MicroBooNE (2410.18419v3)

Published 24 Oct 2024 in hep-ex

Abstract: Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low energy ($<$3~MeV) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV ${208}$Tl decay $\gamma$~rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of ${208}$Tl in the fiberglass composing these struts, $(11.7 \pm 0.2 ~\text{(stat)} \pm 3.1~\text{(syst)})$~Bq/kg. Cosmogenically-produced blips above 3~MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated CORSIKA cosmic ray simulations, suggesting either incorrect CORSIKA modeling of incident cosmic fluxes or particle transport modeling issues in Geant4.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (70)
  1. C. Anderson et al. (ArgoNeuT), The ArgoNeuT detector in the NuMI low-energy beam line at Fermilab, J. Instrum. 7, P10019 (2012).
  2. R. Acciarri et al. (MicroBooNE), Design and construction of the MicroBooNE detector, J. Instrum. 12, P02017 (2017a).
  3. R. Acciarri et al. (LArIAT), The Liquid Argon In A Testbeam (LArIAT) Experiment, J. Instrum. 15, P04026 (2020a).
  4. P. Abratenko et al. (ICARUS), ICARUS at the Fermilab Short-Baseline Neutrino program: initial operation, Eur. Phys. J. C 83, 467 (2023a).
  5. R. Acciarri et al. (MicroBooNE), Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC, J. Instrum. 12, P08003 (2017b).
  6. R. Acciarri et al. (ArgoNeuT), Demonstration of MeV-scale physics in liquid argon time projection chambers using ArgoNeuT, Phys. Rev. D 99, 012002 (2019).
  7. P. Abratenko et al. (MicroBooNE), Demonstration of neutron identification in neutrino interactions in the MicroBooNE liquid argon time projection chamber, Eur. Phys. J. C 84, 1052 (2024a).
  8. A. Friedland and S. W. Li, Understanding the energy resolution of liquid argon neutrino detectors, Phys. Rev. D 99, 036009 (2019).
  9. A. A. Aguilar-Arevalo et al. (MiniBooNE), Updated MiniBooNE neutrino oscillation results with increased data and new background studies, Phys. Rev. D 103, 052002 (2021).
  10. P. Abratenko et al. (MicroBooNE), Search for Neutrino-Induced Neutral-Current ΔΔ\Deltaroman_Δ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess under a Single-Photon Hypothesis, Phys. Rev. Lett. 128, 111801 (2022a).
  11. P. Abratenko et al. (MicroBooNE), Search for an anomalous excess of inclusive charged-current νesubscript𝜈𝑒\nu_{e}italic_ν start_POSTSUBSCRIPT italic_e end_POSTSUBSCRIPT interactions in the MicroBooNE experiment using Wire-Cell reconstruction, Phys. Rev. D 105, 112005 (2022b).
  12. P. Abratenko et al. (MicroBooNE), Search for an anomalous excess of charged-current νesubscript𝜈𝑒\nu_{e}italic_ν start_POSTSUBSCRIPT italic_e end_POSTSUBSCRIPT interactions without pions in the final state with the MicroBooNE experiment, Phys. Rev. D 105, 112004 (2022c).
  13. P. Abratenko et al. (MicroBooNE), Differential cross section measurement of charged current νesubscript𝜈𝑒\nu_{e}italic_ν start_POSTSUBSCRIPT italic_e end_POSTSUBSCRIPT interactions without final-state pions in MicroBooNE, Phys. Rev. D 106, L051102 (2022d).
  14. P. Abratenko et al. (MicroBooNE), Measurement of neutral current single π0superscript𝜋0\pi^{0}italic_π start_POSTSUPERSCRIPT 0 end_POSTSUPERSCRIPT production on argon with the MicroBooNE detector, Phys. Rev. D 107, 012004 (2023b).
  15. P. Abratenko et al. (MicroBooNE Collaboration), Inclusive cross section measurements in final states with and without protons for charged-current νμsubscript𝜈𝜇{\nu}_{\mu}italic_ν start_POSTSUBSCRIPT italic_μ end_POSTSUBSCRIPT-ar scattering in microboone, Phys. Rev. D 110, 013006 (2024b).
  16. P. Abratenko et al. (MicroBooNE Collaboration), First simultaneous measurement of differential muon-neutrino charged-current cross sections on argon for final states with and without protons using microboone data, Phys. Rev. Lett. 133, 041801 (2024c).
  17. P. Abratenko et al. (MicroBooNE), Measurement of double-differential cross sections for mesonless charged-current muon neutrino interactions on argon with final-state protons using the MicroBooNE detector,   (2024d), arXiv:2403.19574 [hep-ex] .
  18. O. Benevides Rodrigues, Search for NuMI μ𝜇\muitalic_μDAR Electron Neutrinos in MicroBooNE, Ph.D. thesis, Syracuse U. (2022), FERMILAB-THESIS-2022-19.
  19. C. Grant and B. Littlejohn, Opportunities With Decay-At-Rest Neutrinos From Decay-In-Flight Neutrino Beams, PoS ICHEP2016, 483 (2016).
  20. R. Harnik, K. J. Kelly, and P. A. N. Machado, Prospects of Measuring Oscillated Decay-at-Rest Neutrinos at Long Baselines, Phys. Rev. D 101, 033008 (2020).
  21. P. A. Machado, O. Palamara, and D. W. Schmitz, The Short-Baseline Neutrino Program at Fermilab, Ann. Rev. Nucl. Part. Sci. 69, 363 (2019).
  22. S. Andringa et al., Low-energy physics in neutrino LArTPCs, J. Phys. G 50, 033001 (2023).
  23. B. Abi et al. (DUNE), Supernova neutrino burst detection with the Deep Underground Neutrino Experiment, Eur. Phys. J. C 81, 423 (2021).
  24. S. Kubota et al. (Q-Pix), Enhanced low-energy supernova burst detection in large liquid argon time projection chambers enabled by Q-Pix, Phys. Rev. D 106, 032011 (2022).
  25. S. Amoruso et al. (ICARUS), Measurement of the μ𝜇\muitalic_μ decay spectrum with the ICARUS liquid argon TPC, Eur. Phys. J. C 33, 233 (2004).
  26. R. Acciarri et al. (MicroBooNE), Michel electron reconstruction using cosmic-ray data from the MicroBooNE LArTPC, J. Instrum. 12, P09014 (2017c).
  27. R. Acciarri et al. (ArgoNeuT), Improved Limits on Millicharged Particles Using the ArgoNeuT Experiment at Fermilab, Phys. Rev. Lett. 124, 131801 (2020b).
  28. A. Bhat, MeV Scale Physics in MicroBooNE, Ph.D. thesis, Syracuse University (2021), FERMILAB-THESIS-2021-14.
  29. MicroBooNE Collaboration, Study of Reconstructed 39Ar Beta Decays at the MicroBooNE Detector, MICROBOONE-NOTE-1050-PUB  (2018).
  30. MicroBooNE Collaboration, Mev-scale physics in microboone, MICROBOONE-NOTE 1076-PUB  (2024).
  31. P. Abratenko (MicroBooNE), Observation of radon mitigation in MicroBooNE by a liquid argon filtration system, J. Instrum. 17, P11022 (2022).
  32. P. Abratenko et al. (MicroBooNE), Measurement of ambient radon progeny decay rates and energy spectra in liquid argon using the MicroBooNE detector, Phys. Rev. D 109, 052007 (2024e).
  33. M. A. Hernandez-Morquecho et al. (LArIAT), Measurements of Pion and Muon Nuclear Capture at Rest on Argon in the LArIAT Experiment,   (2024), arXiv:2408.05133 [hep-ex] .
  34. W. Foreman et al. (LArIAT), Calorimetry for low-energy electrons using charge and light in liquid argon, Phys. Rev. D 101, 012010 (2020).
  35. The Gund Company, NEMA Grade G-10 Glass Epoxy Laminate, https://thegundcompany.com/wp-content/uploads/2016/11/NEMA-G10-EPGC-201-from-The-Gund-Co.pdf.
  36. C. Adams et al. (MicroBooNE), Ionization electron signal processing in single phase LArTPCs. Part I. Algorithm Description and quantitative evaluation with MicroBooNE simulation, J. Instrum. 13, P07006 (2018a).
  37. C. Adams et al. (MicroBooNE), Ionization electron signal processing in single phase LArTPCs. Part II. Data/simulation comparison and performance in MicroBooNE, J. Instrum. 13, P07007 (2018b).
  38. E. Snider and G. Petrillo, LArSoft: toolkit for simulation, reconstruction and analysis of liquid argon TPC neutrino detectors, J. Phys. Conf. Ser. 898, 042057 (2017).
  39. B. Baller, Liquid argon TPC signal formation, signal processing and reconstruction techniques, J. Instrum. 12, P07010 (2017).
  40. T. Sumner, Experimental Searches for Dark Matter, Living Rev. Relativ. 5, 4 (2002).
  41. M. Auger et al. (EXO-200), Search for Neutrinoless Double-Beta Decay in 136Xe with EXO-200, Phys. Rev. Lett. 109, 032505 (2012).
  42. D. S. Akerib et al. (LZ), LUX-ZEPLIN (LZ) Conceptual Design Report,   (2015), arXiv:1509.02910 [physics.ins-det] .
  43. S. I. Alvis et al. (Majorana), Multisite event discrimination for the Majorana demonstrator, Phys. Rev. C 99, 065501 (2019).
  44. J. Dunger and S. D. Biller, Multi-site Event Discrimination in Large Liquid Scintillation Detectors, Nucl. Instrum. Meth. A 943, 162420 (2019).
  45. V. Fischer et al., Measurement of the neutron capture cross-section on argon, Phys. Rev. D 99, 103021 (2019).
  46. P. Abratenko et al. (MicroBooNE), Novel approach for evaluating detector-related uncertainties in a LArTPC using MicroBooNE data, Eur. Phys. J. C 82, 454 (2022e).
  47. P. Abratenko et al. (MicroBooNE), Measurement of the longitudinal diffusion of ionization electrons in the MicroBooNE detector, J. Instrum. 16, P09025 (2021a).
  48. P. Abratenko et al. (MicroBooNE), Measurement of the atmospheric muon rate with the MicroBooNE Liquid Argon TPC, J. Instrum. 16 (04), P04004.
  49. P. Adhikari et al. (DEAP), Precision measurement of the specific activity of 39Ar in atmospheric argon with the DEAP-3600 detector, Eur. Phys. J. C 83, 642 (2023).
  50. P. Benetti et al. (WARP), Measurement of the specific activity of Ar-39 in natural argon, Nucl. Instrum. Meth. A 574, 83 (2007).
  51. National Nuclear Data Center (NNDC), Brookhaven National Laboratory, NuDat 3.0 Database (2024).
  52. P. Novella et al. (NEXT), Measurement of radon-induced backgrounds in the NEXT double beta decay experiment, JHEP 10, 112.
  53. D. Adey et al. (Daya Bay), A high precision calibration of the nonlinear energy response at Daya Bay, Nucl. Instrum. Meth. A 940, 230 (2019).
  54. G. Bellini et al. (Borexino), New experimental limits on the Pauli forbidden transitions in C-12 nuclei obtained with 485 days Borexino data, Phys. Rev. C 81, 034317 (2010).
  55. J. B. Albert et al. (EXO-200), Search for Majorana neutrinos with the first two years of EXO-200 data, Nature 510, 229 (2014).
  56. M. Andriamirado et al. (PROSPECT), Improved short-baseline neutrino oscillation search and energy spectrum measurement with the PROSPECT experiment at HFIR, Phys. Rev. D 103, 032001 (2021).
  57. P. Abratenko et al. (MicroBooNE), Measurement of the longitudinal diffusion of ionization electrons in the MicroBooNE detector, J. Instrum. 16, P09025 (2021c).
  58. R. Acciarri et al. (ArgoNeuT), A study of electron recombination using highly ionizing particles in the ArgoNeuT Liquid Argon TPC, J. Instrum. 8, P08005 (2013).
  59. C. Adams et al. (MicroBooNE), Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons, J. Instrum. 15, P03022 (2020).
  60. P. Abratenko et al. (MicroBooNE), Measurement of space charge effects in the MicroBooNE LArTPC using cosmic muons, J. Instrum. 15, P12037 (2020).
  61. Pacific Northwest National Laboratory and SNOLAB, radiopurity.org (2024).
  62. I. Lawson and B. Cleveland, Low background counting at SNOLAB, AIP Conf. Proc. 1338, 68 (2011).
  63. C. Arpesella et al. (BOREXINO), Measurements of extremely low radioactivity levels in BOREXINO, Astropart. Phys. 18, 1 (2002).
  64. S. Gardiner, Simulating low-energy neutrino interactions with MARLEY, Comput. Phys. Commun. 269, 108123 (2021).
  65. J. Asaadi et al., Physics Opportunities in the ORNL Spallation Neutron Source Second Target Station Era, in Snowmass 2021 (2022) arXiv:2209.02883 [hep-ex] .
  66. A. A. Aguilar-Arevalo et al., Physics Opportunities at a Beam Dump Facility at PIP-II at Fermilab and Beyond,   (2023), arXiv:2311.09915 [hep-ex] .
  67. C. Hagmann, D. Lange, and D. Wright, Cosmic-ray shower generator (CRY) for monte carlo transport codes, in 2007 IEEE Nuclear Science Symposium Conference Record, Vol. 2 (2007) pp. 1143–1146.
  68. MicroBooNE Collaboration, Cosmic shielding studies at microboone, MICROBOONE-NOTE-1005-PUB  (2016).
  69. B. Bhandari et al. (CAPTAIN), First Measurement of the Total Neutron Cross Section on Argon Between 100 and 800 MeV, Phys. Rev. Lett. 123, 042502 (2019).
  70. S. Martynenko et al. (CAPTAIN), Measurement of the neutron cross section on argon between 95 and 720 MeV, Phys. Rev. D 107, 072009 (2023).

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 3 posts and received 2 likes.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up to View

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

Explore Trending Papers

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube