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Title: Inelastic dark matter in light of DAMA/LIBRA

Journal Article · · Physical Review. D, Particles Fields
;  [1];  [2];  [3]
  1. Center for Cosmology and Particle Physics, Department of Physics, New York University, New York, New York 10003 (United States)
  2. Department of Physics and Institute of Theoretical Science, University of Oregon, Eugene, Oregon 97403 (United States)
  3. Department of Physics, Williams College, Williamstown, Massachusetts 01267 (United States)

Inelastic dark matter, in which weakly interacting massive particle (WIMP)-nucleus scatterings occur through a transition to an excited WIMP state {approx}100 keV above the ground state, provides a compelling explanation of the DAMA annual modulation signal. We demonstrate that the relative sensitivities of various dark matter direct detection experiments are modified such that the DAMA annual modulation signal can be reconciled with the absence of a reported signal at CDMS-Soudan, XENON10, ZEPLIN, CRESST, and KIMS for inelastic WIMPs with masses O(100 GeV). We review the status of these experiments, and make predictions for upcoming ones. In particular, we note that inelastic dark matter leads to highly suppressed signals at low energy, with most events typically occurring between 20 and 45 keV (unquenched) at xenon and iodine experiments, and generally no events at low ({approx}10 keV) energies. Suppressing the background in this high-energy region is essential to testing this scenario. The recent CRESST data suggest seven observed tungsten events, which is consistent with expectations from this model. If the tungsten signal persists at future CRESST runs, it would provide compelling evidence for inelastic dark matter, while its absence should exclude it.

OSTI ID:
21266302
Journal Information:
Physical Review. D, Particles Fields, Vol. 79, Issue 4; Other Information: DOI: 10.1103/PhysRevD.79.043513; (c) 2009 The American Physical Society; Country of input: International Atomic Energy Agency (IAEA); ISSN 0556-2821
Country of Publication:
United States
Language:
English

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