Use of event-level neutrino telescope data in global fits for theories of new physics

TL;DR

This paper introduces a fast likelihood method incorporating event-level neutrino data into global physics model fits, demonstrated with supersymmetric models using IceCube data, improving parameter constraints and model exclusion capabilities.

Contribution

It presents a novel, efficient likelihood approach that includes spectral and angular neutrino data for global fits, now available in DarkSUSY 5.0.6, enhancing model analysis accuracy.

Findings

Method accurately recovers mock signals

Spectral information improves parameter constraints

IceCube can probe most of the CMSSM focus-point region

Abstract

We present a fast likelihood method for including event-level neutrino telescope data in parameter explorations of theories for new physics, and announce its public release as part of DarkSUSY 5.0.6. Our construction includes both angular and spectral information about neutrino events, as well as their total number. We also present a corresponding measure for simple model exclusion, which can be used for single models without reference to the rest of a parameter space. We perform a number of supersymmetric parameter scans with IceCube data to illustrate the utility of the method: example global fits and a signal recovery in the constrained minimal supersymmetric standard model (CMSSM), and a model exclusion exercise in a 7-parameter phenomenological version of the MSSM. The final IceCube detector configuration will probe almost the entire focus-point region of the CMSSM, as well as a number of MSSM-7 models that will not otherwise be accessible to e.g. direct detection. Our method accurately recovers the mock signal, and provides tight constraints on model parameters and derived quantities. We show that the inclusion of spectral information significantly improves the accuracy of the recovery, providing motivation for its use in future IceCube analyses.