Abstract: Neutrino mass generation through the Higgs mechanism not only suggests the need to reconsider the physics of electroweak symmetry breaking from a new perspective, but also provides a new theoretically consistent and experimentally viable paradigm. We illustrate this by describing the main features of the electroweak symmetry breaking sector of the simplest type-II seesaw model with spontaneous breaking of lepton number. After reviewing the relevant `theoretical' and astrophysical restrictions on the Higgs sector, we perform an analysis of the sensitivities of Higgs Boson searches at the ongoing ATLAS and CMS experiments at the LHC, including not only the new contributions to the decay channels present in the standard model (SM) but also genuinely non-SM Higgs Boson decays, such as `invisible' Higgs Boson decays to majorons. We find sensitivities that are likely to be reached at the upcoming run of the experiments.

Abstract: The KM3NeT Collaboration is building and operating two deep sea neutrino telescopes at the bottom of the Mediterranean Sea. The telescopes consist of latices of photomultiplier tubes housed in pressure-resistant glass spheres, called digital optical modules and arranged in vertical detection units. The two main scientific goals are the determination of the neutrino mass ordering and the discovery and observation of high-energy neutrino sources in the Universe. Neutrinos are detected via the Cherenkov light, which is induced by charged particles originated in neutrino interactions. The photomultiplier tubes convert the Cherenkov light into electrical signals that are acquired and timestamped by the acquisition electronics. Each optical module houses the acquisition electronics for collecting and timestamping the photomultiplier signals with one nanosecond accuracy. Once finished, the two telescopes will have installed more than six thousand optical acquisition nodes, completing one of the more complex networks in the world in terms of operation and synchronization. The embedded software running in the acquisition nodes has been designed to provide a framework that will operate with different hardware versions and functionalities. The hardware will not be accessible once in operation, which complicates the embedded software architecture. The embedded software provides a set of tools to facilitate remote manageability of the deployed hardware, including safe reconfiguration of the firmware. This paper presents the architecture and the techniques, methods and implementation of the embedded software running in the acquisition nodes of the KM3NeT neutrino telescopes. Program summary Program title: Embedded software for the KM3NeT CLB CPC Library link to program files: https://doi.org/10.17632/s847hpsns4.1 Licensing provisions: GNU General Public License 3 Programming language: C Nature of problem: The challenge for the embedded software in the KM3NeT neutrino telescope lies in orchestrating the Digital Optical Modules (DOMs) to achieve the synchronized data acquisition of the incoming optical signals. The DOMs are the crucial component responsible for capturing neutrino interactions deep underwater. The embedded software must configure and precisely time the operation of each DOM. Any deviation or timing mismatch could compromise data integrity, undermining the scientific value of the experiment. Therefore, the embedded software plays a critical role in coordinating, synchronizing, and operating these modules, ensuring they work in unison to capture and process neutrino signals accurately, ultimately advancing our understanding of fundamental particles in the Universe. Solution method: The embedded software on the DOMs provides a solution based on a C-based bare-metal application, operating without a real-time embedded OS. It is loaded into the RAM during FPGA configuration, consuming less than 256 kB of RAM. The software architecture comprises two layers: system software and application. The former offers OS-like features, including a multitasking scheduler, firmware updates, peripheral drivers, a UDP-based network stack, and error handling utilities. The application layer contains a state machine ensuring consistent program states. It is navigated via slow control events, including external inputs and autonomous responses. Subsystems within the application code control specific acquisition electronics components via the associated driver abstractions. Additional comments including restrictions and unusual features: Due to the operation conditions of the neutrino telescope, where access is restricted, the embedded software implements a fail-safe procedure to reconfigure the firmware where the embedded software runs.

Abstract: We calculate neutrino emissivities from self-annihilating dark matter (DM) (chi) in the dense and hot stellar interior of a (proto)neutron star. Using a model where DM interacts with nucleons in the stellar core through a pseudoscalar boson (a) we find that the neutrino production rates from the dominant reaction channels chi -> nu(nu) over bar or chi chi -> aa, with subsequent decay of the mediator a -> nu(nu) over bar, could locally match and even surpass those of the standard neutrinos from the modified nuclear URCA processes at early ages. We find that the emitting region can be localized in a tiny fraction of the star (less than a few percent of the core volume) and the process can last its entire lifetime for some cases under study. We discuss the possible consequences of our results for stellar cooling in light of existing DM constraints.

Abstract: The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.

Abstract: Collapsing supermassive stars (M greater than or similar to 3 x 10(4) M-circle dot) at high redshifts can naturally provide seeds and explain the origin of the supermassive black holes observed in the centers of nearly all galaxies. During the collapse of supermassive stars, a burst of non-thermal neutrinos is generated with a luminosity that could greatly exceed that of a conventional core collapse supernova explosion. In this work, we investigate the extent to which the neutrinos produced in these explosions can be observed via coherent elastic neutrino-nucleus scattering (CEvNS). Large scale direct dark matter detection experiments provide particularly favorable targets. We find that upcoming O(100) tonne-scale experiments will be sensitive to the collapse of individual supermassive stars at distances as large as O(10) Mpc.