Abstract: Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs.

Abstract: We present the results of the most complete scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm, augmented by the BAMBI neural network machine-learning package. This is the first study to separate out low-mass isotopes (p, (p) over bar and He) from the usual light elements (Be, B, C, N, and O). We find that the propagation parameters that best-fit p, (p) over bar, and He data are significantly different from those that fit light elements, including the B/C and Be-10/Be-9 secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests that each set of species is probing a very different interstellar medium, and that the standard approach of calibrating propagation parameters using B/C can lead to incorrect results. We present posterior distributions and best-fit parameters for propagation of both sets of nuclei, as well as for the injection abundances of elements from H to Si. The input GALDEF files with these new parameters will be included in an upcoming public GALPROP update.

Abstract: A symmetry-preserving approach to the continuum bound-state problem in quantum field theory is used to calculate the masses, leptonic decay constants and light-front distribution amplitudes of empirically accessible heavy-light mesons. The inverse moment of the B-meson distribution is particularly important in treatments of exclusive B-decays using effective field theory and the factorisation formalism; and its value is therefore computed: lambda(B) = (zeta = 2GeV) = 0.54(3) GeV. As an example and in anticipation of precision measurements at new-generation B-factories, the branching fraction for the rare B -> gamma (E-gamma)l nu(l) radiative decay is also calculated, retaining 1/m(B)(2), and 1/E-gamma(2) corrections to the differential decay width, with the result Gamma(B -> gamma l nu l) /Gamma(B) = 0.47 (15) on E-gamma > 1.5 GeV.

Abstract: Methods: For Ir-192, I-125, and Pd-103, the authors considered from two to five published spectra. Spherical sources approximating common brachytherapy sources were assessed. Kerma and dose results from GEANT4, MCNP5, and PENELOPE-2008 were compared for water and air. The dosimetric influence of Ir-192, I-125, and Pd-103 spectral choice was determined. Results: For the spectra considered, there were no statistically significant differences between kerma or dose results based on Monte Carlo code choice when using the same spectrum. Water-kerma differences of about 2%, 2%, and 0.7% were observed due to spectrum choice for Ir-192, I-125, and Pd-103, respectively (independent of radial distance), when accounting for photon yield per Bq. Similar differences were observed for air-kerma rate. However, their ratio (as used in the dose-rate constant) did not significantly change when the various photon spectra were selected because the differences compensated each other when dividing dose rate by air-kerma strength. Conclusions: Given the standardization of radionuclide data available from the National Nuclear Data Center (NNDC) and the rigorous infrastructure for performing and maintaining the data set evaluations, NNDC spectra are suggested for brachytherapy simulations in medical physics applications.

Abstract: This paper presents the electron and photon energy calibration obtained with the ATLAS detector using about 36 fb(-1) of LHC proton-proton collision data recorded at root s = 13 TeV in 2015 and 2016. The different calibration steps applied to the data and the optimization of the reconstruction of electron and photon energies are discussed. The absolute energy scale is set using a large sample of Z boson decays into electron-positron pairs. The systematic uncertainty in the energy scale calibration varies between 0.03% to 0.2% in most of the detector acceptance for electrons with transverse momentum close to 45 GeV. For electrons with transverse momentum of 10 GeV the typical uncertainty is 0.3% to 0.8% and it varies between 0.25% and 1% for photons with transverse momentum around 60 GeV. Validations of the energy calibration with J/psi -> e(+)e(-) decays and radiative Z boson decays are also presented.