Abstract: Gamow-Teller (GT) transitions are the most common weak interaction processes of spin-isospin (sigma tau) type in atomic nuclei. They are of interest not only in nuclear physics but also in astrophysics; they play an important role in supernovae explosions and nucleosynthesis. The direct study of weak decay processes, however, gives relatively limited information about GT transitions and the states excited via GT transitions (GT states); beta decay can only access states at excitation energies lower than the decay Q-value, and neutrino-induced reactions have very small cross-sections. However, one should note that beta decay has a direct access to the absolute GT transition strengths B(GT) from a study of half-lives, Q(beta)-values and branching ratios. They also provide information on GT transitions in nuclei far-from-stability. Studies of M1 gamma transitions provide similar information. In contrast, the complementary charge-exchange (CE) reactions, such as the (p, n) or ((3)He, t) reactions at intermediate beam energies and 0 degrees, can selectively excite GT states up to high excitation energies in the final nucleus. It has been found empirically that there is a close proportionality between the cross-sections at 0 degrees and the transition strengths B(GT) in these CE reactions. Therefore, CE reactions are useful tools to study the relative values of B(GT) strengths up to high excitation energies. In recent ((3)He, t) measurements, one order-of-magnitude improvement in the energy resolution has been achieved. This has made it possible to make one-to-one comparisons of GT transitions studied in CE reactions and beta decays. Thus GT strengths in ((3)He, t) reactions can be normalised by the beta-decay values. In addition, comparisons with closely related M1 transitions studied in gamma decay or electron inelastic scattering [(e, e')1, and furthermore with “spin” M I transitions that can be studied by proton inelastic scattering [(p, p')[ have now been made possible. In these comparisons, the isospin quantum number T and associated symmetry structure in the same mass A nuclei (isobars) play a key role. Isospin symmetry can extend our scope even to the structures of unstable nuclei that are far from reach at present unstable beam factories.

Abstract: DTAS is a segmented total absorption y-ray spectrometer developed for the DESPEC experiment at FAIR. It is composed of up to eighteen NaI(Tl) crystals. In this work we study the performance of this detector with laboratory sources and also under real experimental conditions. We present a procedure to reconstruct offline the sum of the energy deposited in all the crystals of the spectrometer, which is complicated by the effect of NaI(Tl) light-yield non-proportionality. The use of a system to correct for time variations of the gain in individual detector modules, based on a light pulse generator, is demonstrated. We describe also an event-based method to evaluate the summing-pileup electronic distortion in segmented spectrometers. All of this allows a careful characterization of the detector with Monte Carlo simulations that is needed to calculate the response function for the analysis of total absorption gamma-ray spectroscopy data. Special attention was paid to the interaction of neutrons with the spectrometer, since they are a source of contamination in studies of beta-delayed neutron emitting nuclei.

Abstract: Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses.