Simple and statistically sound recommendations for analysing physical theories

Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo.

Exploring the 2HDM with Global Fits in GAMBIT

In this work, we present preliminary results of a global fit of the typeII two-Higgs-doublet model (2HDM) with the tool GAMBIT. Our study includes various constraints, including the theoretical constraints (unitarity, perturbativity and vacuum stability), Higgs searches at colliders, electroweak physics and flavour constraints. With the latest experimental results, our results not only confirm past studies but also go further in probing the model. We find, for example, that the measurements of B→K*µ+µ− angular observables cannot be explained in the type-II 2HDM.

Minimal 4D Composite Higgs Models Under Current LHC Constraints

We present preliminary results of the first convergent global fits of several minimal composite Higgs models. Our fits are performed using the differential evolution optimisation package Diver. A variety of physical constraints are taken into account, including a wide range of exclusion bounds on heavy resonance production from Run 2 of the LHC. As a by-product of the fits, we analyse the collider phenomenology of the lightest new up-type and downtype resonances in the viable regions of our models, finding some low-mass resonances that can be probed in future collider searches.

Model independent determination of the dark matter mass from direct detection experiments

Determining the dark matter (DM) mass is of paramount importance for understanding dark matter. We present a novel parametrization of the DM speed distribution which will allow the DM mass to be accurately measured using data from weakly interacting massive particle (WIMP) direct detection experiments. Specifically, we parametrize the natural logarithm of the speed distribution as a polynomial in the speed v. We demonstrate, using mock data from upcoming experiments, that by fitting the WIMP mass and interaction cross section, along with the polynomial coefficients, we can accurately reconstruct both the WIMP mass and speed distribution. This new method is the first demonstration that an accurate, unbiased reconstruction of the WIMP mass is possible without prior assumptions about the distribution function. We anticipate that this technique will be invaluable in the analysis of future experimental data.