Missing energy look-alikes with 100 pb-1 at the LHC
Jay Hubisz, Joseph Lykken, Maurizio Pierini, Maria Spiropulu
TL;DR
The paper tackles the problem of identifying the underlying theory after an early missing-energy discovery at the LHC, using a strategy built on robust ratios of inclusive counts across multiple trigger boxes. By populating a theory space with SUSY, Little Higgs, and UED look-alikes and defining a comprehensive set of observables (including $m_{T2}$ and hemisphere/cone analyses), the authors demonstrate that many look-alikes can be distinguished with around 100–1000 pb$^{-1}$ of data, often with $>5\sigma$ significance. A key finding is that $m_{T2}$-based ratios, which are relatively insensitive to spin at leading order, combine with jet/muon observables to reveal spin-driven differences and mass hierarchies, enabling discrimination even in small data samples. The study provides a concrete, robust framework for early LHC data to resolve the LHC Inverse Problem, guiding follow-up measurements and informing the physics interpretation of any missing-energy excess. The methodology emphasizes realism, cross-checks, and validation prospects with CMS data, and sets the stage for integrating more models and refined background estimates as data accumulate.
Abstract
A missing energy discovery is possible at the LHC with the first 100 pb-1 of understood data. We present a realistic strategy to rapidly narrow the list of candidate theories at, or close to, the moment of discovery. The strategy is based on robust ratios of inclusive counts of simple physics objects. We study specific cases showing discrimination of look-alike models in simulated data sets that are at least 10 to 100 times smaller than used in previous studies. We discriminate supersymmetry models from non-supersymmetric look-alikes with only 100 pb-1 of simulated data, using combinations of observables that trace back to differences in spin.
