Abstract: We introduce FlexibleSUSY, a Mathematica and C++ package, which generates a fast, precise C++ spectrum generator for any SUSY model specified by the user. The generated code is designed with both speed and modularity in mind, making it easy to adapt and extend with new features. The model is specified by supplying the superpotential, gauge structure and particle content in a SARAH model file; specific boundary conditions e.g. at the GUT, weak or intermediate scales are defined in a separate FlexibleSUSY model file. From these model files, FlexibleSUSY generates C++ code for self-energies, tadpole corrections, renormalization group equations (RGEs) and electroweak symmetry breaking (EWSB) conditions and combines them with numerical routines for solving the RGEs and EWSB conditions simultaneously. The resulting spectrum generator is then able to solve for the spectrum of the model, including loop-corrected pole masses, consistent with user specified boundary conditions. The modular structure of the generated code allows for individual components to be replaced with an alternative if available. FlexibleSUSY has been carefully designed to grow as alternative solvers and calculators are added. Predefined models include the MSSM, NMSSM, E6SSM, USSM, R-symmetric models and models with right-handed neutrinos. Program Summary Program title: FlexibleSUSY Catalogue identifier: AEVIv10 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEVIv10.html obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 129406 No. of bytes in distributed program, including test data, etc.: 854831 Distribution format: tar.gz Programming language: C++, Wolfram/Mathematica, FORTRAN, Bourne shell. Computer: Personal computer. Operating system: Tested on Linux 3.x, Mac OS X. Classification: 11.1, 11.6, 6.5. External routines: SARAH 4.0.4, Boost library, Eigen, LAPACK Nature of problem: Determining the mass spectrum and mixings for any supersymmetric model. The generated code must find simultaneous solutions to constraints which are specified at two or more different renormalization scales, which are connected by renormalization group equations forming a large set of coupled first-order differential equations. Solution method: Nested iterative algorithm and numerical minimization of the Higgs potential. Restrictions: The couplings must remain perturbative at all scales between the highest and the lowest boundary condition. FlexibleSUSY assumes that all couplings of the model are real (i.e. CP-conserving). Due to the modular nature of the generated code, adaption and extension to overcome restrictions in scope is quite straightforward. Running time: 0.06-0.2 seconds per parameter point.

Abstract: The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between tracktype and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project. Program summary Program Title: gSeaGen CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1 Licensing provisions: GPLv3 Programming language: C++ External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL [3]. Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using modern and maintained neutrino interaction simulation libraries which include the state-of-the-art physics models. The default application is the simulation of neutrino interactions within KM3NeT [4]. Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is considered as a reference code within the neutrino community. Additional comments including restrictions and unusual features: The code was tested with GENIE version 2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic to the code but due to the present GENIE valid energy range. References: [1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87. [2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357. [3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070. [4] S. Adrian-Martinez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.

Abstract: Spectroscopy is used to measure the elemental abundances in the outer layers of the Sun, whereas helioseismology probes the interior. It is well known that current spectroscopic determinations of the chemical composition are starkly at odds with the metallicity implied by helioseismology. We investigate whether the discrepancy may be due to conversion of photons to a new light boson in the solar photosphere. We examine the impact of particles with axion-like interactions with the photon on the inferred photospheric abundances, showing that resonant axion-photon conversion is not possible in the region of the solar atmosphere in which line formation occurs. Although non-resonant conversion in the line-forming regions can in principle impact derived abundances, constraints from axion-photon conversion experiments rule out the couplings necessary for these effects to be detectable. We show that this extends to hidden photons and chameleons (which would exhibit similar phenomenological behaviour), ruling out known theories of new light bosons as photospheric solutions to the solar abundance problem.

Abstract: In the past decade, a new class of bright transient radio sources with millisecond duration has been discovered. The origin of these so-called fast radio bursts (FRBs) is still a mystery, despite the growing observational efforts made by various multiwavelength and multimessenger facilities. To date, many models have been proposed to explain FRBs, but neither the progenitors nor the radiative and the particle acceleration processes at work have been clearly identified. In this paper, we assess whether hadronic processes may occur in the vicinity of the FRB source. If they do, FRBs may contribute to the high-energy cosmic-ray and neutrino fluxes. A search for these hadronic signatures was carried out using the ANTARES neutrino telescope. The analysis consists in looking for high-energy neutrinos, in the TeV-PeV regime, that are spatially and temporally coincident with the detected FRBs. Most of the FRBs discovered in the period 2013-2017 were in the field of view of the ANTARES detector, which is sensitive mostly to events originating from the Southern hemisphere. From this period, 12 FRBs were selected and no coincident neutrino candidate was observed. Upper limits on the per-burst neutrino fluence were derived using a power-law spectrum, dN/DE nu proportional to E-nu(-gamma), for the incoming neutrino flux, assuming spectral indexes gamma = 1.0, 2.0, 2.5. Finally, the neutrino energy was constrained by computing the total energy radiated in neutrinos, assuming different distances for the FRBs. Constraints on the neutrino fluence and on the energy released were derived from the associated null results.

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.