Digging for Dark Matter: Spectral Analysis and Discovery Potential of Paleo-Detectors

Thomas D. P. Edwards, Bradley J. Kavanagh, Christoph Weniger, Sebastian Baum, Andrzej K. Drukier +3 more
11/26/2018
hep-phastro-ph.COastro-ph.IM

No official code found. Best implementation: bradkav/WIMpy_NREFT (13 stars, MIT, last commit 2024-10-30).

Abstract

Paleo-detectors are a recently proposed method for the direct detection of Dark Matter (DM). In such detectors, one would search for the persistent damage features left by DM--nucleus interactions in ancient minerals. Initial sensitivity projections have shown that paleo-detectors could probe much of the remaining Weakly Interacting Massive Particle (WIMP) parameter space. In this paper, we improve upon the cut-and-count approach previously used to estimate the sensitivity by performing a full spectral analysis of the background- and DM-induced signal spectra. We consider two scenarios for the systematic errors on the background spectra: i) systematic errors on the normalization only, and ii) systematic errors on the shape of the backgrounds. We find that the projected sensitivity is rather robust to imperfect knowledge of the backgrounds. Finally, we study how well the parameters of the true WIMP model could be reconstructed in the hypothetical case of a WIMP discovery.

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Code Implementations(1)

bradkav/WIMpy_NREFTCommunity100%
MIT

WIMpy_NREFT is a code for calculating Dark Matter direct detection rates in the framework of non-relativistic effective field theory (NREFT).

138Shell, PythonJul 24, 20171 years agoMIT

Cite this paper

@article{edwards2018digging,
  title  = {Digging for Dark Matter: Spectral Analysis and Discovery Potential of Paleo-Detectors},
  author = {Thomas D. P. Edwards and Bradley J. Kavanagh and Christoph Weniger and Sebastian Baum and Andrzej K. Drukier and Katherine Freese and Maciej Górski and Patrick Stengel},
  year   = {2018},
  eprint = {1811.10549},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1811.10549}
}

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