[en] With the origin of the astropysical neutrinos observed by IceCube not being completely resolved, a closer look at possible sources is needed. A recent analysis by the IceCube Collaboration suggests that blazars detected by Fermi are responsible for less than a third of the observed neutrino flux. Research by Broderick et al. considers plasma beam instabilities in a more generalised model for the EGRB leading to a more fitting blazar distribution in the unified AGN-Paradigm. For Very High Energy Gamma-Rays this distribution leads to a diffuse flux matching the Fermi data. The goal of the presented work is to calculate the diffuse neutrino flux supposedly generated by unresolved blazars based on the assumptions made by Broderick et al. for the Extragalactic Gamma-Ray Background using new data. This is then compared to the diffuse flux measured by IceCube. This talk presents an outline of the methodology used to calculate the neutrino flux from the suggested Blazar distribution.

[en] The aim of the work presented in this talk is to measure the atmospheric electron neutrino spectrum on data collected by the IceCube Detector. IceCube is a Cherenkov neutrino detector instrumenting 1 km${}^3$ of ice at the South Pole. The Cherenkov light detected by IceCube is emitted by charged particles like atmospheric muons or the secondary particles of neutrino interactions passing through the detector. Events caused by neutrinos result in different event topologies, depending on the neutrino flavor and the kind of interaction. The events this analysis is interested in, the interaction of electron neutrinos, have a spherical topology in the detector. These events are referred to as cascade-like events. Muons, either atmospheric or from muon neutrino interactions, show an elongated event topology and are referred to as track-like events. The first part of this analysis is to build an event sample containing a high amount of cascade-like events with low amounts of track-like events, utilizing machine learning methods. Subsequently an unfolding approach will be used to obtain to the atmospheric electron neutrino spectrum. This analysis is currently planned to encompass one year of data from the year 2012, however a extension to multiple years may be possible in the near future. This talk will give an overview over the current status of this analysis and its prospects.

[en] IceCube is a neutrino observatory located at the South Pole, consisting of digital optical modules that detect Cherenkov light emitted from charged particles traversing the Antarctic ice sheet. The most dominant source of background in the search for neutrinos are atmospheric muons produced in interactions of cosmic rays in the upper atmosphere. At a trigger rate of about 3000 Hz, they also provide a valuable source of information about cosmic rays. A special subset of atmospheric muon events are muon events that contain only muon tracks that end within the detector volume. These stopping muons exhibit features that have interesting implications for both cosmic-ray physics and calibration purposes. In order to extract a sample of stopping muons of high purity, a supervised machine learning approach is used. In this talk, an overview of the employed methods is given. The properties of the extracted sample are discussed, and an unfolding of the muon range spectrum is presented.