ترغب بنشر مسار تعليمي؟ اضغط هنا

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

91   0   0.0 ( 0 )
 نشر من قبل John Marshall
 تاريخ النشر 2017
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

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.



قيم البحث

اقرأ أيضاً

We describe algorithms developed to isolate and accurately reconstruct two-track events that are contained within the MicroBooNE detector. This method is optimized to reconstruct two tracks of lengths longer than 5 cm. This code has applications to s earches for neutrino oscillations and measurements of cross sections using quasi-elastic-like charged current events. The algorithms we discuss will be applicable to all detectors running in Fermilabs Short Baseline Neutrino program (SBN), and to any future liquid argon time projection chamber (LArTPC) experiment with beam energies ~1 GeV. The algorithms are publicly available on a GITHUB repository. This reconstruction offers a complementary and independent alternative to the Pandora reconstruction package currently in use in LArTPC experiments, and provides similar reconstruction performance for two-track events.
The OPERA experiment discovered muon neutrino into tau neutrino oscillations in appearance mode, detecting tau leptons by means of nuclear emulsion films. The apparatus was also endowed with electronic detectors with tracking capability, such as scin tillator strips and resistive plate chambers. Because of its location, in the underground Gran Sasso laboratory, under 3800 m.w.e., the OPERA detector has also been used as an observatory for TeV muons produced by cosmic rays in the atmosphere. In this paper the measurement of the single muon flux modulation and of its correlation with the seasonal variation of the atmospheric temperature are reported.
264 - P. Abratenko , M. Alrashed , R. An 2019
We present upper limits on the production of heavy neutral leptons (HNLs) decaying to $mu pi$ pairs using data collected with the MicroBooNE liquid-argon time projection chamber (TPC) operating at Fermilab. This search is the first of its kind perfor med in a liquid-argon TPC. We use data collected in 2017 and 2018 corresponding to an exposure of $2.0 times 10^{20}$ protons on target from the Fermilab Booster Neutrino Beam, which produces mainly muon neutrinos with an average energy of $approx 800$ 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 $lvert U_{mu4}rvert^2$ of the extended PMNS mixing matrix in the range $lvert U_{mu4}rvert^2<(6.6$-$0.9)times 10^{-7}$ for Dirac HNLs and $lvert U_{mu4}rvert^2<(4.7$-$0.7)times 10^{-7}$ for Majorana HNLs, assuming HNL masses between $260$ and $385$ MeV and $lvert U_{e 4}rvert^2 = lvert U_{tau 4}rvert^2 = 0$.
112 - V.I.Galkin 2008
We develop a new discrimination procedure for separating electron neutrinos from muon neutrinos, based on detailed simulations carried out with GEANT3.21 and with mean angular distribution functions and their relative fluctuations. Using our procedur e we are able to discriminate muons from electrons in Fully Contained Events in Super-Kamioknade Experiment with a probability of error ofless than several %. Also we have checked geometrical resolution on both cases, considering only the ring-like structure of the Cherenkov image and a geometrical reconstruction procedure utilizing the full distribution. Even the methodologically correct approach we have adopted, we cannot reproduce the accuracies for particle discrimination, momentum resolution, interaction vertex location, and angular resolution obtained by the Super-Kamiokande Collaboration.
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 mu ons 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 $epsilon_{mathrm{data}}=(97.1pm0.1~(mathrm{stat}) pm 1.4~(mathrm{sys}))%$, in good agreement with the Monte Carlo reconstruction efficiency $epsilon_{mathrm{MC}} = (97.4pm0.1)%$. 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.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا