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Search for a diffuse flux of astrophysical muon neutrinos with the IceCube 59-string configuration
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arxiv 1311.7048 v1 pith:PXOOEBMS submitted 2013-11-27 astro-ph.HE
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abstract
A search for high-energy neutrinos was performed using data collected by the IceCube Neutrino Observatory from May 2009 to May 2010, when the array was running in its 59-string configuration. The data sample was optimized to contain muon neutrino induced events with a background contamination of atmospheric muons of less than 1%. These data, which are dominated by atmospheric neutrinos, are analyzed with a global likelihood fit to search for possible contributions of prompt atmospheric and astrophysical neutrinos, neither of which have yet been identified. Such signals are expected to follow a harder energy spectrum than conventional atmospheric neutrinos. In addition, the zenith angle distribution differs for astrophysical and atmospheric signals. A global fit of the reconstructed energies and directions of observed events is performed, including possible neutrino flux contributions for an astrophysical signal and atmospheric backgrounds as well as systematic uncertainties of the experiment and theoretical predictions. The best fit yields an astrophysical signal flux for $\nu_\mu + \bar\nu_\mu $ of $E^2 \cdot \Phi (E) = 0.25 \cdot 10^{-8} \textrm{GeV} \textrm{cm}^{-2} \textrm{s}^{-1} \textrm{sr}^{-1}$, and a zero prompt component. Although the sensitivity of this analysis for astrophysical neutrinos surpasses the Waxman and Bahcall upper bound, the experimental limit at 90% confidence level is a factor of 1.5 above at a flux of $E^2 \cdot \Phi (E) = 1.44 \cdot 10^{-8} \textrm{GeV} \textrm{cm}^{-2} \textrm{s}^{-1} \textrm{sr}^{-1}$.
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Analysing Ultra High Energy Cosmic Rays' Anisotropy in $\boldsymbol{f(R, T)}$ Gravity Theory
astro-ph.HE 2024-12 conditional novelty 4.0 of 10
Under f(R,T) gravity models, the predicted dipole anisotropy of diffusive UHECRs is lower than under ΛCDM, and with tuned magnetic field and source distance both fit Pierre Auger data.
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