Abstract: The highest-energy known gamma-ray sources are all located within 0.degrees 5 of extremely powerful pulsars. This raises the question of whether ultra-high-energy (UHE; >56 TeV) gamma-ray emission is a universal feature expected near pulsars with a high spin-down power. Using four years of data from the High Altitude Water Cherenkov Gamma-Ray Observatory, we present a joint-likelihood analysis of 10 extremely powerful pulsars to search for subthreshold UHE gamma-ray emission correlated with these locations. We report a significant detection (>3 sigma), indicating that UHE gamma-ray emission is a generic feature of powerful pulsars. We discuss the emission mechanisms of the gamma rays and the implications of this result. The individual environment, such as the magnetic field and particle density in the surrounding area, appears to play a role in the amount of emission.

Abstract: Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events like Monte Carlo generators. We study three processes: a simple two-body decay, the processes e(+)e(-)-> Z -> l(+)l(-) and pp -> tt<mml:mo><overbar></mml:mover> including the decay of the top quarks and a simulation of the detector response. By buffering density information of encoded Monte Carlo events given the encoder of a Variational Autoencoder we are able to construct a prior for the sampling of new events from the decoder that yields distributions that are in very good agreement with real Monte Carlo events and are generated several orders of magnitude faster. Applications of this work include generic density estimation and sampling, targeted event generation via a principal component analysis of encoded ground truth data, anomaly detection and more efficient importance sampling, e.g., for the phase space integration of matrix elements in quantum field theories. Here, the authors report buffered-density variational autoencoders for the generation of physical events. This method is computationally less expensive over other traditional methods and beyond accelerating the data generation process, it can help to steer the generation and to detect anomalies.

Abstract: The excess of electron-like events measured by MiniBooNE challenges our understanding of neutrinos and their interactions. We review the status of this open problem and ongoing efforts to resolve it. After introducing the experiment and its results, we consider the main experimental backgrounds and the related physics of neutrino interactions with matter, such as quasielastic-like scattering and weak pion production on nucleons and nuclei. Special attention is paid to single photon emission in neutral current interactions and, in particular, its coherent channel. The difficulties to reconcile the MiniBooNE anomaly with global oscillation analysis is then highlighted. We finally outline some of the proposed solutions of the puzzle involving unconventional neutrino-interaction mechanisms.