Search

The leading contribution to the uncertainties of atmospheric neutrino flux calculations arise from the cosmic-ray nucleon flux and the production cross sections of secondary particles in hadron-air interactions. The data-driven model developed in this work parametrizes particle yields from fixed-target accelerator data. The propagation of errors from the accelerator data to the inclusive muon and neutrino flux predictions results in smaller uncertainties than in previous estimates, and the description of atmospheric flux data is good. The model is implemented as part of the MCEq package, and hence can be flexibly employed for theoretical flux error estimation at neutrino telescopes., Comment: 22 pages, 17 figures

High-energy astrophysical neutrinos, discovered by IceCube, are now regularly observed, albeit at a low rate due to their low flux. As a result, open questions about high-energy neutrino astrophysics and particle physics remain limited by statistics at best, or unanswered at worst. Fortunately, this situation will improve soon: in the next few years, a host of new neutrino telescopes, currently under planning and construction, will come online. It is natural to combine their collected observing power: we propose the Planetary Neutrino Monitoring System (PLE$\nu$M), a concept for a global repository of high-energy neutrino observations, in order to finally give firm answers to open questions. PLE$\nu$M will reach up to four times the exposure available today by combining the exposures of current and future neutrino telescopes distributed around the world -- IceCube, IceCube-Gen2, Baikal-GVD, KM3NeT, and P-ONE. Depending on the declination and spectral index, PLE$\nu$M will improve the sensitivity to astrophysical neutrinos by up to two orders of magnitude. We present first estimates on the capability of PLE$\nu$M to discover Galactic and extragalactic sources of astrophysical neutrinos and to characterize the diffuse flux of high-energy neutrinos in unprecedented detail., Comment: Presented at the 37th International Cosmic Ray Conference (ICRC 2021). 8 pages, 5 figures

Located at the South Pole, the IceCube Neutrino Observatory is the world largest neutrino telescope, instrumenting one cubic kilometre of Antarctic ice at a depth between 1450m to 2450m. In 2013 IceCube reported the first observations of a diffuse astrophysical high-energy neutrino flux. Although the IceCube Collaboration has identified more than 100 high-energy neutrino events, the origin of this neutrino flux is still not known. Blazars, a subclass of Active Galactic Nuclei and one of the most powerful classes of objects in the Universe, have long been considered promising sources of high energy neutrinos. A blazar origin of this high-energy neutrino flux can be examined using stacking methods testing the correlation between IceCube neutrinos and catalogs of hypothesized sources. Here we present the results of a stacking analysis for 1301 blazars from the third catalog of hard \textit{Fermi}-LAT sources (3FHL). The analysis is performed on 8 years of through-going muon data from the Northern Hemisphere, recorded by IceCube between 2009 and 2016. No excess of neutrinos from the blazar position was found and first limits on the neutrino production of these sources will be shown., Comment: Presented at the 36th International Cosmic Ray Conference (ICRC 2019). See arXiv:1907.11699 for all IceCube contributions

Electromagnetic-Cascades (EmCa) is a Python package for the simulation of electromagnetic cascades in various materials. The showers are modeled using cascade equations and the relevant interactions, specifically pair production, Bremsstrahlung, Compton scattering and ionization. This methodology has the advantage of being computationally inexpensive and fast, unlike Monte Carlo methods. The code includes low and high energy material effects, allowing for a high range of validity of the simulation results. EmCa is easily extendable and offers a framework for testing different electromagnetic interaction models. In combination with MCEq, a Python package for hadronic particle showers using cascade equations, full simulations of atmospheric fluxes can be done., Comment: Disagreement between authors

Purpose: The data which is available to surgeons before, during and after surgery is steadily increasing in quantity as well as diversity. When planning a patient's treatment, this large amount of information can be difficult to interpret. To aid in processing the information, new methods need to be found to present multi-modal patient data, ideally combining textual, imagery, temporal and 3D data in a holistic and context-aware system. Methods: We present an open-source framework which allows handling of patient data in a virtual reality (VR) environment. By using VR technology, the workspace available to the surgeon is maximized and 3D patient data is rendered in stereo, which increases depth perception. The framework organizes the data into workspaces and contains tools which allow users to control, manipulate and enhance the data. Due to the framework's modular design, it can easily be adapted and extended for various clinical applications. Results: The framework was evaluated by clinical personnel (77 participants). The majority of the group stated that a complex surgical situation is easier to comprehend by using the framework, and that it is very well suited for education. Furthermore, the application to various clinical scenarios - including the simulation of excitation-propagation in the human atrium - demonstrated the framework's adaptability. As a feasibility study, the framework was used during the planning phase of the surgical removal of a large central carcinoma from a patient's liver. Conclusion: The clinical evaluation showed a large potential and high acceptance for the VR environment in a medical context. The various applications confirmed that the framework is easily extended and can be used in real-time simulation as well as for the manipulation of complex anatomical structures., Comment: This is a post-peer-review, pre-copyedit version of an article published in the International Journal of Computer Assisted Radiology and Surgery (IJCARS). The final authenticated version is available online at: https://doi.org/10.1007/s11548-018-1730-x

We consider the sum of the incurred start-up costs of a single unit in a Unit Commitment problem. Our major result is a correspondence between the facets of its epigraph and some binary trees for concave start-up cost functions CU, which is bijective if CU is strictly concave. We derive an exponential H-representation of this epigraph, and provide an exact linear separation algorithm. These results significantly reduce the integrality gap of the Mixed Integer formulation of a Unit Commitment Problem compared to current literature., Comment: 28 pages, preprint

This paper presents an improved mixed-integer model for the Thermal Unit Commitment Problem. By introducing new variables for the temperature of each thermal unit, the off-time-dependent start-up costs are modeled accurately and with a lower integrality gap than state-of-the-art formulations. This new approach significantly improves computational efficiency compared to existing formulations, even if they only model a rough approximation of the start-up costs. Our findings were validated on real-world test cases using CPLEX., Comment: 9 pages, 5 figures, 1 table, data sets

We consider resonances in the Pauli-Fierz model of non-relativistic QED. We use and slightly modify the analysis developed by Bach, Froehlich, and Sigal to obtain an upper and lower bound on the lifetime of quasi-stationary states.