2015
DOI: 10.1016/j.astropartphys.2014.09.003
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Statistical issues in astrophysical searches for particle dark matter

Abstract: In this review statistical issues appearing in astrophysical searches for particle dark matter, i.e. indirect detection (dark matter annihilating into standard model particles) or direct detection (dark matter particles scattering in deep underground detectors) are discussed. One particular aspect of these searches is the presence of very large uncertainties in nuisance parameters (astrophysical factors) that are degenerate with parameters of interest (mass and annihilation/decay cross sections for the particl… Show more

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Cited by 41 publications
(39 citation statements)
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“…We found a detection for the 0.5-8 keV image of SDSS J0813 + 3508 with p = 0.0108, which becomes less significant (the p-value increases to p = 0.0832) after taking into account the number of tests we have performed (e.g. Conrad 2015). We then compared the radio and X-ray images of SDSS J0813 + 3508, and did not find extended Xray structure that corresponds to the radio jet, as shown in Fig.…”
Section: Future Workmentioning
confidence: 78%
“…We found a detection for the 0.5-8 keV image of SDSS J0813 + 3508 with p = 0.0108, which becomes less significant (the p-value increases to p = 0.0832) after taking into account the number of tests we have performed (e.g. Conrad 2015). We then compared the radio and X-ray images of SDSS J0813 + 3508, and did not find extended Xray structure that corresponds to the radio jet, as shown in Fig.…”
Section: Future Workmentioning
confidence: 78%
“…This suggests fundamental limitations to the spherical Jeans modeling which is common in the field (although see [32] for Jfactors computed using axisymmetric Jeans modeling). In particular, increasingly sophisticated statistical techniques [70,71] will fail to include an inherent uncertainty if the assumption of a spherical stellar density profiles in a spherical dark halo breaks down. The uncertainties, which are different for different dSphs, must be accounted for joint analyses of multiple dSphs.…”
Section: Discussionmentioning
confidence: 99%
“…with x max/min = (D/r0) cos θ ± (rt/r0) 2 − (D/r0) 2 sin 2 θ; rt is the cutoff radius of the system, usually assumed to the the tidal radius (Binney & Tremaine 2008 where Θ represents the nuisance parameters array. The final point results in the profile likelihood curve of J, with which the statistical inference can be performed (Conrad 2014). Specifically, the maximum likelihood estimate (MLE) of J and its uncertainty can be determined.…”
Section: Methodsmentioning
confidence: 99%