scholarly journals Analyzing Direct Dark Matter Detection Data by the AMIDAS Website

2012 ◽  
Vol 53 ◽  
pp. 77-88 ◽  
Author(s):  
C.-L. Shan
2021 ◽  
Vol 2021 (12) ◽  
pp. 048
Author(s):  
Muping Chen ◽  
Graciela B. Gelmini ◽  
Volodymyr Takhistov

Abstract Sub-GeV mass dark matter particles whose collisions with nuclei would not deposit sufficient energy to be detected, could instead be revealed through their interaction with electrons. Analyses of data from direct detection experiments usually require assuming a local dark matter halo velocity distribution. In the halo-independent analysis method, properties of this distribution are instead inferred from direct dark matter detection data, which allows then to compare different data without making any assumption on the uncertain local dark halo characteristics. This method has so far been developed for and applied to dark matter scattering off nuclei. Here we demonstrate how this analysis can be applied to scattering off electrons.


2017 ◽  
Vol 888 ◽  
pp. 012207
Author(s):  
G. Angloher ◽  
P. Carniti ◽  
L. Cassina ◽  
L. Gironi ◽  
C. Gotti ◽  
...  

2014 ◽  
Vol 2014 (11) ◽  
pp. 002-002 ◽  
Author(s):  
D. Cogollo ◽  
Alma X. Gonzalez-Morales ◽  
Farinaldo S. Queiroz ◽  
P. Rebello Teles

2012 ◽  
Vol 36 (6) ◽  
pp. 505-512 ◽  
Author(s):  
Ya-Zheng Chen ◽  
Jun-Mou Chen ◽  
Yan-An Luo ◽  
Hong Shen ◽  
Xue-Qian Li

2014 ◽  
Vol 29 (05) ◽  
pp. 1450014 ◽  
Author(s):  
Sen Miao ◽  
Chung-Lin Shan ◽  
Yu-Feng Zhou

In this paper, we introduce model-independent data analysis procedures for identifying inelastic WIMP-nucleus scattering as well as for reconstructing the mass and the mass splitting of inelastic WIMPs simultaneously and separately. Our simulations show that, with 𝒪(50) observed WIMP signals from one experiment, one could already distinguish the inelastic WIMP scattering scenarios from the elastic one. By combining two or more data sets with positive signals, the WIMP mass and the mass splitting could even be reconstructed with statistical uncertainties of less than a factor of two.


2015 ◽  
Vol 2015 (7) ◽  
Author(s):  
Daniele Barducci ◽  
Alexander Belyaev ◽  
Aoife K. M. Bharucha ◽  
Werner Porod ◽  
Veronica Sanz

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