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The IceCube Observatory at the South Pole allows the measurement of thediffuse neutrino flux. The assumption of specific flux parametrizations limitsthe range of spectral shapes. Given the increasing statistics of the datarecorded, model-independent unfolding approaches can overcome theselimitations. In this contribution, a model-independent approach to estimate themuon neutrino flux between 125 GeV and 2.5 PeV is presented. In order toextract muon neutrinos from the data taken by the detector, amachine-learning-based method is employed. This yields an efficient muonneutrino sample with a purity of over 99 %. The spectrum is estimated by aLikelihood-based unfolding technique involving a novel binning scheme using adecision tree on three years of IceCube data. This measurement provides thefirst model-independent muon neutrino spectrum for multiple years in thisenergy regime.

Model-independent Measurement of the Atmospheric Muon Neutrino Energy Spectrum up to 2.5 PeV