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Surrogate Models for Direct Dark Matter Detection

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 Added by Andrew Cheek
 Publication date 2018
  fields Physics
and research's language is English




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In this work we introduce RAPIDD, a surrogate model that speeds up the computation of the expected spectrum of dark matter particles in direct detection experiments. RAPIDD replaces the exact calculation of the dark matter differential rate (which in general involves up to three nested integrals) with a much faster parametrization in terms of ordinary polynomials of the dark matter mass and couplings, obtained in an initial training phase. In this article, we validate our surrogate model on the multi-dimensional parameter space resulting from the effective field theory description of dark matter interactions with nuclei, including also astrophysical uncertainties in the description of the dark matter halo. As a concrete example, we use this tool to study the complementarity of different targets to discriminate simplified dark matter models. We demonstrate that RAPIDD is fast and accurate, and particularly well-suited to explore a multi-dimensional parameter space, such as the one in effective field theory approach, and scans with a large number of evaluations.



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We provide a Mathematica package, DirectDM, that takes as input the Wilson coefficients of the relativistic effective theory describing the interactions of dark matter with quarks, gluons and photons, and matches it onto an effective theory describing the interactions of dark matter with neutrons and protons. The nonperturbative matching is performed at leading order in a chiral expansion. The one-loop QCD and QED renormalization-group evolution from the electroweak scale down to the hadronic scale, as well as finite corrections at the heavy quark thresholds are taken into account. We also provide an interface with the package DMFormFactor so that, starting from the relativistic effective theory, one can directly obtain the event rates for direct detection experiments.
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