Supersymmetry and Dark Matter in Light of LHC 2010 and Xenon100 Data
O. Buchmueller, R. Cavanaugh, D. Colling, A. De Roeck, M.J. Dolan,, J.R. Ellis, H. Flacher, S. Heinemeyer, G. Isidori, D. Martinez Santos, K.A., Olive, S. Rogerson, F.J. Ronga, and G. Weiglein

TL;DR
This paper performs a comprehensive frequentist analysis of supersymmetric models using 2010 LHC and Xenon100 data, updating favored parameter regions and dark matter predictions, and discussing implications for future colliders.
Contribution
It provides the first combined analysis of LHC and Xenon100 results on several supersymmetric models, refining their parameter spaces and dark matter scattering predictions.
Findings
Heavier mass spectra are favored by LHC data.
Dark matter scattering cross sections are smaller, near pre-LHC ranges.
Updated sparticle mass predictions impact future collider searches.
Abstract
We make frequentist analyses of the CMSSM, NUHM1, VCMSSM and mSUGRA parameter spaces taking into account all the public results of searches for supersymmetry using data from the 2010 LHC run and the Xenon100 direct search for dark matter scattering. The LHC data set includes ATLAS and CMS searches for jets + ETslash events (with or without leptons) and for the heavier MSSM Higgs bosons, and the upper limit on bs to mu mu including data from LHCb as well as CDF and D0. The absences of signals in the LHC data favour somewhat heavier mass spectra than in our previous analyses of the CMSSM, NUHM1 and VCMSSM, and somewhat smaller dark matter scattering cross sections, all close to or within the pre-LHC 68% CL ranges, but do not impact significantly the favoured regions of the mSUGRA parameter space. We also discuss the impact of the Xenon100 constraint on spin-independent dark matter…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
