Predictive Signatures of Supersymmetry: Measuring the Dark Matter Mass and Gluino Mass with Early LHC data
Daniel Feldman, Katherine Freese, Pran Nath, Brent D. Nelson, Gregory, Peim

TL;DR
This paper explores how early LHC data can be used to measure dark matter and gluino masses within a supersymmetric model, showing that these parameters are accessible through simple observables and consistent with current experimental constraints.
Contribution
It demonstrates that early LHC data can determine dark matter and gluino masses in a predictive supersymmetric model using straightforward measurements, with implications for direct detection experiments.
Findings
Dark matter mass is in the range 50-65 GeV
Gluino mass has an upper bound of 575 GeV
All model points are discoverable at 7 TeV LHC
Abstract
We present a focused study of a predictive unified model whose measurable consequences are immediately relevant to early discovery prospects of supersymmetry at the LHC. ATLAS and CMS have released their analysis with 35~pb of data and the model class we discuss is consistent with this data. It is shown that with an increase in luminosity the LSP dark matter mass and the gluino mass can be inferred from simple observables such as kinematic edges in leptonic channels and peak values in effective mass distributions. Specifically, we consider cases in which the neutralino is of low mass and where the relic density consistent with WMAP observations arises via the exchange of Higgs bosons in unified supergravity models. The magnitudes of the gaugino masses are sharply limited to focused regions of the parameter space, and in particular the dark matter mass lies in the range $\sim…
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.
