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Title: Prospects for distinguishing dark matter models using annual modulation

It has recently been demonstrated that, in the event of a putative signal in dark matter direct detection experiments, properly identifying the underlying dark matter-nuclei interaction promises to be a challenging task. Given the most optimistic expectations for the number counts of recoil events in the forthcoming Generation 2 experiments, differentiating between interactions that produce distinct features in the recoil energy spectra will only be possible if a strong signal is observed simultaneously on a variety of complementary targets. However, there is a wide range of viable theories that give rise to virtually identical energy spectra, and may only differ by the dependence of the recoil rate on the dark matter velocity. In this work, we investigate how degeneracy between such competing models may be broken by analyzing the time dependence of nuclear recoils, i.e. the annual modulation of the rate. For this purpose, we simulate dark matter events for a variety of interactions and experiments, and perform a Bayesian model-selection analysis on all simulated data sets, evaluating the chance of correctly identifying the input model for a given experimental setup. Lastly, we find that including information on the annual modulation of the rate may significantly enhance the ability ofmore » a single target to distinguish dark matter models with nearly degenerate recoil spectra, but only with exposures beyond the expectations of Generation 2 experiments.« less
Authors:
ORCiD logo [1] ;  [2] ;  [3]
  1. Univ. of California, Los Angeles, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  2. Institute for Advanced Study, Princeton, NJ (United States)
  3. C. N. Yang Institute for Theoretical Physics, Stony Brook, NY (United States)
Publication Date:
Report Number(s):
FERMILAB-PUB-16-654-A; arXiv:1612.07808
Journal ID: ISSN 1475-7516; 1505708; TRN: US1700684
Grant/Contract Number:
AC02-07CH11359
Type:
Accepted Manuscript
Journal Name:
Journal of Cosmology and Astroparticle Physics
Additional Journal Information:
Journal Volume: 2017; Journal Issue: 02; Journal ID: ISSN 1475-7516
Publisher:
Institute of Physics (IOP)
Research Org:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; dark matter experiments; dark matter theory
OSTI Identifier:
1346365