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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Dark Matter characterization at the LHC in the Effective Field Theory approach

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Belyaev, Alexander ; Panizzi, Luca ; Pukhov, Alexander ; Thomas, Marc
Total Authors: 4
Document type: Journal article
Source: Journal of High Energy Physics; n. 4 APR 19 2017.
Web of Science Citations: 8

We have studied the complete set of dimension 5 and dimension 6 effective operators involving the interaction of scalar, fermion and vector Dark Matter (DM) with SM quarks and gluons, to explore the possibility to distinguish these operators and characterise the spin of DM at the LHC. We have found that three factors - the effective dimension of the operator, the structure of the SM part of the operator and the parton densities of the SM particles connected to the operator - uniquely define the shape of the (unobservable) invariant mass distribution of the DM pair and, consequently, the shape of the (observable) E-T(miss) distribution related to it. Using chi(2) analysis, we found that at the LHC, with a luminosity of 300 fb(-1), certain classes of EFT operators can be distinguished from each other. Hence, since DM spin is partly correlated with the factors defining the shape of E-T(miss), the LHC can potentially shed a light also on DM spin. We have also observed a drastic difference in the efficiencies (up to two orders of magnitude) for large E-T(miss) cuts scenarios with different DM spin, thus indicating that the DM discovery potential strongly depends on it. The study we perform here can be applied more generally than within the EFT paradigm, where the DM mediator is not produced on-the-mass-shell, such as the case of t-channel mediator or mediator with mass below 2 M-DM, where the invariant mass of the DM pair is not fixed. (AU)

FAPESP's process: 11/11973-4 - ICTP South American Institute for Fundamental Research: a regional center for theoretical physics
Grantee:Nathan Jacob Berkovits
Support type: Research Projects - Thematic Grants