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Title: Taking Halo-Independent Dark Matter Methods Out of the Bin

We develop a new halo-independent strategy for analyzing emerging DM hints, utilizing the method of extended maximum likelihood. This approach does not require the binning of events, making it uniquely suited to the analysis of emerging DM direct detection hints. It determines a preferred envelope, at a given confidence level, for the DM velocity integral which best fits the data using all available information and can be used even in the case of a single anomalous scattering event. All of the halo-independent information from a direct detection result may then be presented in a single plot, allowing simple comparisons between multiple experiments. This results in the halo-independent analogue of the usual mass and cross-section plots found in typical direct detection analyses, where limit curves may be compared with best-fit regions in halo-space. The method is straightforward to implement, using already-established techniques, and its utility is demonstrated through the first unbinned halo-independent comparison of the three anomalous events observed in the CDMS-Si detector with recent limits from the LUX experiment.
Authors:
 [1] ;  [2] ;  [2]
  1. Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
  2. Massachusetts Institute of Technology, Cambridge, MA (United States)
Publication Date:
OSTI Identifier:
1155862
Report Number(s):
MIT-CTP-4528; FERMILAB-PUB-14-004-T
Journal ID: ISSN 1475-7516; arXiv eprint number arXiv:1403.6830; TRN: US1500457
Grant/Contract Number:
AC02-07CH11359
Type:
Accepted Manuscript
Journal Name:
Journal of Cosmology and Astroparticle Physics
Additional Journal Information:
Journal Volume: 2014; Journal Issue: 10; Journal ID: ISSN 1475-7516
Publisher:
Institute of Physics (IOP)
Research Org:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; 97 MATHEMATICS AND COMPUTING