Constraints On New Theories Using Rivet

A procedure to set limits on BSM models using unfolded data

Contur is a procedure and toolkit designed to set limits on theories Beyond the Standard Model, using a combined limit derived from comparisons between theoretical simulations and data at the particle-level. That is, the theory simulates a fully-exclusive final state, and the data have been corrected for detector effects. The original procedure is defined in a ‘white paper’ available on the arXiv, which should be used as a reference for this method: arXiv:1606.05296.

Authors:Jonathan Butterworth, David Grellscheid, Michael Krämer, David Yallup
Abstract:A new method providing general consistency constraints for Beyond-the-Standard-Model (BSM) theories, using measurements at particle colliders, is presented. The method, “Constraints On New Theories Using Rivet”, Contur, exploits the fact that particle-level differential measurements made in fiducial regions of phase-space have a high degree of model-independence. These measurements can therefore be compared to BSM physics implemented in Monte Carlo generators in a very generic way, allowing a wider array of final states to be considered than is typically the case. The Contur approach should be seen as complementary to the discovery potential of direct searches, being designed to eliminate inconsistent BSM proposals in a context where many (but perhaps not all) measurements are consistent with the Standard Model. We demonstrate, using a competitive simplified dark matter model, the power of this approach. The Contur method is highly scaleable to other models and future measurements.

Björn Sarrazin has now also joined the Contur team.


What to expect of this page

These pages are intended to be a ‘living status report’ of the Contur project. They define the methodology, and provide an up-to-date archive of the models and datasets tested with the tools. Contur is intended to be easily extensible not just to considering new scenarios, but to the inclusion of additional data in the limit setting process. When particularly significant new models or datasets are added, it is anticipated that further papers will be written and linked as snapshots of progress. But these pages should always contain the most up-to-date status. The text started as a copy of the original paper, but has already evolved significantly.

Contents: