Abstract: We present a supersymmetric left-right model which predicts gauge coupling unification close to the string scale and extra vector bosons at the TeV scale. The subtleties in constructing a model which is in agreement with the measured quark masses and mixing for such a low left-right breaking scale are discussed. It is shown that in the constrained version of this model radiative breaking of the gauge symmetries is possible and a SM-like Higgs is obtained. Additional CP-even scalars of a similar mass or even much lighter are possible. The expected mass hierarchies for the supersymmetric states differ clearly from those of the constrained MSSM. In particular, the lightest down-type squark, which is a mixture of the sbottom and extra vector-like states, is always lighter than the stop. We also comment on the model's capability to explain current anomalies observed at the LHC.

Abstract: We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of similar to 10(4) with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.

Abstract: This paper presents the design of a total absorption gamma-ray spectrometer for the determination of beta-decay intensity distributions of exotic nuclear species at the focal plane of the FAIR-NUSTAR Super Fragment Separator. The spectrometer is a key instrument in the DESPEC experiment and the proposed implementation follows extensive design studies and prototype tests. Two options were contemplated, based on Nal(TI) and LaBr3:Ce inorganic scintillation crystals respectively. Monte Carlo simulations and technical considerations determined the optimal configurations consisting of sixteen 15 x 15 x 25 cm(3) crystals for the Nal(Tl) option and one hundred and twenty-eight 5.5 x 5.5 x 11 cm(3) crystals for the LaBr3:Ce option. Minimization of dead material was crucial for maximizing the spectrometer full-energy peak efficiency. Module prototypes were build to verify constructional details and characterize their performance. The measured energy and timing resolution was found to agree rather well with estimates based on simulations of scintillation light transport and collection. The neutron sensitivity of the spectrometer, important when measuring beta-delayed neutron emitters, was investigated by means of Monte Carlo simulations.

Abstract: Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge.

Abstract: Kohn-Sham density functional calculations are reported for the structures of clusters consisting of a carbonyl sulfide (OCS) molecule with N = 1, 8, 18, and 40 attached He-3 atoms. The N = 1 cluster ground state is highly localized at the molecular waist (donut ring position), but for higher levels of excitation becomes increasingly delocalized. The first magic cluster with 8 atoms has a significant density at both ends of the molecule in addition to the donut ring. With N = 18 He-3 atoms the molecule is enclosed by a magic number closed shell. Another magic stable structure consisting of two nearly isotropically spherical closed shells is found at N = 40. A comparison with calculations for the same sized He-4 clusters show some important similarities, e. g., pile up at the donut ring position but altogether a more diffuse, less anisotropic structure. These results are discussed in the light of the recently analyzed infrared spectra measured in large pure He-3 droplets (N approximate to 1.2 x 10(4)) [B. Sartakov, J. P. Toennies, and A. F. Vilesov, J. Chem. Phys. 136, 134316 (2012)]. The moments of inertia of the 11 atom spherical shell structure, which is consistent with the experimental spectrum, lies between the predicted moments of inertia for N = 8 and N = 18 clusters. Overall the calculations reveal that the structures and energies of small doped He-3 are only slightly more diffuse and less energetic than the same He-4 clusters.