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Grieger, M., Hensel, T., Agramunt, J., Bemmerer, D., Degering, D., Dillmann, I., et al. (2020). Neutron flux and spectrum in the Dresden Felsenkeller underground facility studied by moderated He-3 counters. Phys. Rev. D, 101(12), 123027–15pp.
Abstract: Ambient neutrons may cause significant background for underground experiments. Therefore, it is necessary to investigate their flux and energy spectrum in order to devise a proper shielding. Here, two sets of altogether ten moderated He-3 neutron counters are used for a detailed study of the ambient neutron background in tunnel IV of the Felsenkeller facility, underground below 45 m of rock in Dresden/Germany. One of the moderators is lined with lead and thus sensitive to neutrons of energies higher than 10 MeV. For each He-3 counter moderator assembly, the energy-dependent neutron sensitivity was calculated with the FLUKA code. The count rates of the ten detectors were then fitted with the MAXED and GRAVEL packages. As a result, both the neutron energy spectrum from 10(-9) to 300 MeV and the flux integrated over the same energy range were determined experimentally. The data show that at a given depth, both the flux and the spectrum vary significantly depending on local conditions. Energy-integrated fluxes of (0.61 +/- 0.05), (1.96 +/- 0.15), and (4.6 +/- 0.4) x 10(-4) cm(-2) s(-1), respectively, are measured for three sites within Felsenkeller tunnel IV which have similar muon flux but different shielding wall configurations. The integrated neutron flux data and the obtained spectra for the three sites are matched reasonably well by FLUKA Monte Carlo calculations that are based on the known muon flux and composition of the measurement room walls.
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Algora, A., Ganioglu, E., Sarriguren, P., Guadilla, V., Fraile, L. M., Nacher, E., et al. (2021). Total absorption gamma-ray spectroscopy study of the beta-decay of Hg-186. Phys. Lett. B, 819, 136438–7pp.
Abstract: The Gamow-Teller strength distribution of the decay of Hg-186 into Au-186 has been determined for the first time using the total absorption gamma spectroscopy technique and has been compared with theoretical QRPA calculations using the SLy4 Skyrme force. The measured Gamow-Teller strength distribution and the half-life are described by mixing oblate and prolate configurations independently in the parent and daughter nuclei. In this theoretical framework the best description of the experimental beta strength is obtained with dominantly prolate components for both parent Hg-186 and daughter Au-186. The approach also allowed us to determine an upper limit of the oblate component in the parent state. The complexity of the analysis required the development of a new approach in the analysis of the X-ray gated total absorption spectrum.
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Bhattacharya, S., Sil, A., Roshan, R., & Vatsyayan, D. (2022). Symmetry origin of baryon asymmetry, dark matter, and neutrino mass. Phys. Rev. D, 106(7), 075005–10pp.
Abstract: We propose a minimal model based on lepton number symmetry (and violation), to address a common origin of baryon asymmetry, dark matter and neutrino mass generation. The model consists of a vectorlike fermion to constitute the dark sector, three right-handed neutrinos (RHNs) to dictate leptogenesis and neutrino mass, while an additional complex scalar is assumed to be present in the early Universe the decay of which produces both dark matter and RHNs via lepton number violating and lepton number conserving interactions respectively. Interestingly, the presence of the same scalar helps in making the electroweak vacuum stable until the Planck scale. The unnatural largeness and smallness of the parameters required to describe correct experimental limits are attributed to lepton number violation. The allowed parameter space of the model is illustrated via a numerical scan.
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Angles-Alcazar, D., Genel, S., Marinacci, F., Spergel, D. N., et al. (2022). Inferring Halo Masses with Graph Neural Networks. Astrophys. J., 935(1), 30–15pp.
Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Genel, S., Angles-Alcazar, D., Hernquist, L., Marinacci, F., et al. (2023). Weighing the Milky Way and Andromeda galaxies with artificial intelligence. Phys. Rev. D, 107(10), 103003–8pp.
Abstract: We present new constraints on the masses of the halos hosting the Milky Way and Andromeda galaxies derived using graph neural networks. Our models, trained on 2,000 state-of-the-art hydrodynamic simulations of the CAMELS project, only make use of the positions, velocities and stellar masses of the galaxies belonging to the halos, and are able to perform likelihood-free inference on halo masses while accounting for both cosmological and astrophysical uncertainties. Our constraints are in agreement with estimates from other traditional methods, within our derived posterior standard deviation.
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