Abstract

We present an improved event-level likelihood formalism for including neutrino telescope data in global fits to new physics. We derive limits on spin-dependent dark matter-proton scattering by employing the new formalism in a re-analysis of data from the 79-string IceCube search for dark matter annihilation in the Sun, including explicit energy information for each event. The new analysis excludes a number of models in the weak-scale minimal supersymmetric standard model (MSSM) for the first time. This work is accompanied by the public release of the 79-string IceCube data, as well as an associated computer code for applying the new likelihood to arbitrary dark matter models.

Highlights

  • The IceCube detectorCompleted in December 2010, the IceCube neutrino observatory [23] is a neutrino telescope situated at the South Pole

  • Background estimationAs in Paper I, the background distributions for each event selection come directly from data

  • We have presented a new analysis of data collected in the 79-string IceCube search for dark matter, taking into account energies of individual neutrino events

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Summary

The IceCube detector

Completed in December 2010, the IceCube neutrino observatory [23] is a neutrino telescope situated at the South Pole. IceCube is installed in the glacial ice at depths of between 1450 m and 2450 m, instrumenting a total volume of one cubic kilometre. In its 79-string configuration, 73 strings have a horizontal spacing of 125 m and a vertical spacing of 17 m between DOMs. The six remaining strings are located near the central string of IceCube and feature a reduced vertical spacing between DOMs of 7 m and higher quantum efficiency photomultiplier tubes. Along with the seven surrounding regular strings, they form the DeepCore subarray [24]. The horizontal distance between strings in DeepCore is less than 75 m. The higher sensor density in clear ice provides an order of magnitude lower energy threshold of O(10) GeV compared to the main IceCube array

Data samples
Signal and background simulation
Calculation of detector efficiencies
Angular response
Energy estimator
Background estimation
General form
Background likelihood
Signal likelihood
Detector response
Predicted event rate
Bias factor calculation
Improved limits on WIMP dark matter
Implications for MSSM benchmarks
Findings
Conclusions
Full Text
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