1. Prospect of dark matter searches in split SUSY models
- Author
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Hieu Minh Tran and Nobuchika Okada
- Subjects
Physics ,History ,Particle physics ,Dark matter ,Supersymmetry ,Computer Science Applications ,Education - Abstract
The results from the XENON1T/Panda-X and IceCube experiments have set severe upper limits on spin-independent (SI) and spin-dependent (SD) scattering cross section of weakly interacting massive particles on nuclei. In the framework of split supersymmetry scenario supported by the LHC constraints, we investigate the prospect of dark matter (DM) direct and indirect detection experiments. Assuming a relation among gaugino masses at the grand unification scale, we have specified the parameter regions that predict the right DM relic abundance as well as satisfy the constraints on SI and SD scattering cross sections of DM. In the case of universal gaugino masses, the XENON1T/Panda-X results have ruled out completely the well-tempered neutralino region. We have found that 200 times smaller than the current IceCube bound is the sensitivity limit that a future DM indirect detection experiment should have at least in order to have a certain impact beyond the current XENON1T/Panda-X results. The future results from XENON1T will be able to test a signification portion of the Higgsino-like region. Although there are points in the Higgsino-like region that cannot be reached by future DM detection experiments, direct production channels of neutralino/chargino can be used to test the model at the LHC/HL-HLC. In the case of non-universal gaugino masses, beside showing the allowed parameter space, we have specified the regions that can be tested at both future DM direct and indirect detection experiments. One of them are Higgsino-like region, while the others two predict a well mixed bino-wino DM. The DM properties in each region have been examined and demonstrated with a benchmark of-ino spectrum. Interestingly, points in the mixed bino-wino region with rather light chargino can be tested the LHC 14 TeV.
- Published
- 2020
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