Abstract: This manuscript summarizes the results of radiative neutron capture cross-section measurements on two stable germanium isotopes, Ge-70 and Ge-73. Experiments were performed at the n_TOF facility at CERN via the time-of-flight technique, over a wide neutron energy range, for all stable germanium isotopes (70,72,73,74, and 76). Results for Ge-70 [Phys. Rev. C 100, 045804 (2019)] and Ge-73 [Phys. Lett. B 790, 458 (2019)] are already published. In the field of nuclear structure, such measurements allow to study excited levels close to the neutron binding energy and to obtain information on nuclear properties. In stellar nucleosynthesis research, neutron induced reactions on germanium are of importance for nucleosynthesis in the weak component of the slow neutron capture processes.

Abstract: The Ge-72(n, gamma) cross section was measured for neutron energies up to 300 keV at the neutron time-of-flight facility n_TOF (CERN), Geneva, for the first time covering energies relevant to heavy-element synthesis in stars. The measurement was performed at the high-resolution beamline EAR-1, using an isotopically enriched (GeO2)-Ge-72 sample. The prompt capture gamma rays were detected with four liquid scintillation detectors, optimized for low neutron sensitivity. We determined resonance capture kernels up to a neutron energy of 43 keV, and averaged cross sections from 43 to 300 keV. Maxwellian-averaged cross section values were calculated from kT = 5 to 100 keV, with uncertainties between 3.2% and 7.1%. The new results significantly reduce uncertainties of abundances produced in the slow neutron capture process in massive stars.

Abstract: Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of <similar to> 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.

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.

Abstract: We conjecture that the proper-time series expansion of the one-loop effective Lagrangian of quantum electrodynamics can be summed in all terms containing the field-strength invariants F = 1/4F F-mu nu(mu nu) (x), G = 1/4 (F) over tilde F-mu nu(mu nu) (x), including those also possessing derivatives of the electromagnetic field strength. This partial resummation is exactly encapsulated in a factor with the same form as the Heisenberg-Euler Lagrangian density, except that now the electric and magnetic fields can depend arbitrarily on spacetime coordinates. We provide strong evidence for this conjecture, which is proved to sixth order in the proper time. Furthermore, and as a byproduct, we generate some solvable electromagnetic backgrounds. We also discuss the implications for a generalization of the Schwinger formula for pair production induced by nonconstant electric fields. Finally, we briefly outline the extension of these results in the presence of gravity.