Soderstrom, P. A. et al, Agramunt, J., Egea, J., Gadea, A., & Huyuk, T. (2019). Neutron detection and gamma-ray suppression using artificial neural networks with the liquid scintillators BC-501A and BC-537. Nucl. Instrum. Methods Phys. Res. A, 916, 238–245.
Abstract: In this work we present a comparison between the two liquid scintillators BC-501A and BC-537 in terms of their performance regarding the pulse-shape discrimination between neutrons and gamma rays. Special emphasis is put on the application of artificial neural networks. The results show a systematically higher gamma-ray rejection ratio for BC-501A compared to BC-537 applying the commonly used charge comparison method. Using the artificial neural network approach the discrimination quality was improved to more than 95% rejection efficiency of gamma rays over the energy range 150 to 1000 keV for both BC-501A and BC-537. However, due to the larger light output of BC-501A compared to BC-537, neutrons could be identified in BC-501A using artificial neural networks down to a recoil proton energy of 800 keV compared to a recoil deuteron energy of 1200 keV for BC-537. We conclude that using artificial neural networks it is possible to obtain the same gamma-ray rejection quality from both BC-501A and BC-537 for neutrons above a low-energy threshold. This threshold is, however, lower for BC-501A, which is important for nuclear structure spectroscopy experiments of rare reaction channels where low-energy interactions dominates.
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PANDA Collaboration(Singh, B. et al), & Diaz, J. (2019). Technical design report for the (P)over-barANDA Barrel DIRC detector. J. Phys. G, 46(4), 045001–155pp.
Abstract: The (P) over bar ANDA (anti-Proton ANnihiliation at DArmstadt) experiment will be one of the four flagship experiments at the new international accelerator complex FAIR (Facility for Antiproton and Ion Research) in Darmstadt, Germany. (P) over bar ANDA will address fundamental questions of hadron physics and quantum chromodynamics using high-intensity cooled antiproton beams with momenta between 1.5 and 15 GeV/c and a design luminosity of up to 2 x 10(32) cm(-2) S-1. Excellent particle identification (PID) is crucial to the success of the (P) over bar ANDA physics program. Hadronic PID in the barrel region of the target spectrometer will be performed by a fast and compact Cherenkov counter using the detection of internally reflected Cherenkov light (DIRC) technology. It is designed to cover the polar angle range from 22 degrees to 140 degrees and will provide at least 3 standard deviations (s.d.) pi/K separation up to 3.5 GeV/c, matching the expected upper limit of the final state kaon momentum distribution from simulation. This documents describes the technical design and the expected performance of the (P) over bar ANDA Barrel DIRC detector. The design is based on the successful BaBar DIRC with several key improvements. The performance and system cost were optimized in detailed detector simulations and validated with full system prototypes using particle beams at GSI and CERN. The final design meets or exceeds the PID goal of clean pi/K separation with at least 3 s.d. over the entire phase space of charged kaons in the Barrel DIRC.
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PANDA Collaboration(Singh, B. et al), & Diaz, J. (2016). Study of doubly strange systems using stored antiprotons. Nucl. Phys. A, 954, 323–340.
Abstract: Bound nuclear systems with two units of strangeness are still poorly known despite their importance for many strong interaction phenomena. Stored antiprotons beams in the GeV range represent an unparalleled factory for various hyperon-antihyperon pairs. Their outstanding large production probability in antiproton collisions will open the floodgates for a series of new studies of systems which contain two or even more units of strangeness at the PANDA experiment at FAIR. For the first time, high resolution gamma-spectroscopy of doubly strange Lambda Lambda-hypernuclei will be performed, thus complementing measurements of ground state decays of Lambda Lambda-hypernuclei at J-PARC or possible decays of particle unstable hypernuclei in heavy ion reactions. High resolution spectroscopy of multistrange Xi(-) -atoms will be feasible and even the production of Omega(-) -atoms will be within reach. The latter might open the door to the vertical bar S vertical bar = 3 world in strangeness nuclear physics, by the study of the hadronic Omega(-) -nucleus interaction. For the first time it will be possible to study the behavior of Xi(+) in nuclear systems under well controlled conditions.
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Simpson, F., Jimenez, R., Pena-Garay, C., & Verde, L. (2018). Dark energy from the motions of neutrinos. Phys. Dark Universe, 20, 72–77.
Abstract: Ordinarily, a scalar field may only play the role of dark energy if it possesses a potential that is either extraordinarily flat or extremely fine-tuned. Here we demonstrate that these restrictions are lifted when the scalar field undergoes persistent energy exchange with another fluid. In this scenario, the field is prevented from reversing its direction of motion, and instead may come to rest while displaced from the local minimum of its potential. Therefore almost any scalar potential is capable of initiating a prolonged phase of cosmic acceleration. If the rate of energy transfer is modulated via a derivative coupling, the field undergoes a rapid process of freezing, after which the field's equation of state mimicks that of a cosmological constant. We present a physically motivated realisation in the form of a neutrino-majoron coupling, which avoids the dynamical instabilities associated with mass-varying neutrino models. Finally we discuss possible means by which this model could be experimentally verified.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
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