Model-Independent Bounds on a Light Higgs

TL;DR

This paper develops a statistical method to accurately interpret LHC data constraints on a generic Higgs parameter space, enabling better identification of viable models and potential new physics signals.

Contribution

It introduces a simple, effective statistical approach to reconstruct likelihood profiles from publicly available data, improving the analysis of Higgs search results.

Findings

The method accurately reconstructs likelihood profiles from limited data.

It helps narrow down the viable parameter space for a Higgs-like scalar.

It facilitates the identification of potential new physics signals.

Abstract

We present up-to-date constraints on a generic Higgs parameter space. An accurate assessment of these exclusions must take into account statistical, and potentially signal, fluctuations in the data currently taken at the LHC. For this, we have constructed a straightforward statistical method for making full use of the data that is publicly available. We show that, using the expected and observed exclusions which are quoted for each search channel, we can fully reconstruct likelihood profiles under very reasonable and simple assumptions. Even working with this somewhat limited information, we show that our method is sufficiently accurate to warrant its study and advocate its use over more naive prescriptions. Using this method, we can begin to narrow in on the remaining viable parameter space for a Higgs-like scalar state, and to ascertain the nature of any hints of new physics---Higgs or otherwise---appearing in the data.