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Probing WIMP particle physics and astrophysics with direct detection and neutrino telescope data

Abstract : With positive signals from multiple direct detection experiments it will, in principle, be possible to measure the mass and cross sections of weakly-interacting massive particle (WIMP) dark matter. Recent work has shown that, with a polynomial parameterisation of the WIMP speed distribution, it is possible to make an unbiased measurement of the WIMP mass, without making any astrophysical assumptions. However, direct detection experiments are not sensitive to low-speed WIMPs and, therefore, any model-independent approach will lead to a bias in the cross section. This problem can be solved with the addition of measurements of the flux of neutrinos from the Sun. This is because the flux of neutrinos produced from the annihilation of WIMPs which have been gravitationally captured in the Sun is sensitive to low-speed WIMPs. Using mock data from next-generation direct detection experiments and from the IceCube neutrino telescope, we show that the complementary information from IceCube on low-speed WIMPs breaks the degeneracy between the cross section and the speed distribution. This allows unbiased determinations of the WIMP mass and spin-independent and spin-dependent cross sections to be made, and the speed distribution to be reconstructed. We use two parameterisations of the speed distribution: binned and polynomial. While the polynomial parameterisation can encompass a wider range of speed distributions, this leads to larger uncertainties in the particle physics parameters.
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Contributor : Emmanuelle De Laborderie Connect in order to contact the contributor
Submitted on : Tuesday, June 21, 2016 - 3:58:05 PM
Last modification on : Monday, December 13, 2021 - 9:16:04 AM

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Bradley J. Kavanagh, Mattia Fornasa, Anne M. Green. Probing WIMP particle physics and astrophysics with direct detection and neutrino telescope data. Physical Review D, American Physical Society, 2015, 91 (10), pp.3533. ⟨10.1103/PhysRevD.91.103533⟩. ⟨cea-01335024⟩



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