Australia

Christopher Chang

Pat Scott

Germany

Tomás Gonzalo

Felix Kahlhoefer

Martin White

Publisher Erratum to: Global fits of simplified models for dark matter with GAMBIT

Global fits explore different parameter regions of a given model and apply constraints obtained at many energy scales. This makes it challenging to perform global fits of simplified models, which may not be valid at high energies. In this study, we derive a unitarity bound for a simplified vector dark matter model with an s-channel vector mediator and apply it to global fits of this model with GAMBIT in order to correctly interpret missing energy searches at the LHC. Two parameter space regions emerge as consistent with all experimental constraints, corresponding to different annihilation modes of the dark matter. We show that although these models are subject to strong validity constraints, they are currently most strongly constrained by measurements less sensitive to the high-energy behaviour of the theory. Understanding when these models cannot be consistently studied will become increasingly relevant as they are applied to LHC Run 3 data.

Global fits of simplified models for dark matter with GAMBIT

Using the GAMBIT global fitting framework, we constrain the MSSM with an eV-scale gravitino as the lightest supersymmetric particle, and the six electroweakinos (neutralinos and charginos) as the only other light new states. We combine 15 ATLAS and 12 CMS searches at 13 TeV, along with a large collection of ATLAS and CMS measurements of Standard Model signatures. This model, which we refer to as the  $${{\tilde{G}}}$$  <math> <mover> <mi>G</mi> <mo>~</mo> </mover> </math>  -EWMSSM, exhibits quite varied collider phenomenology due to its many permitted electroweakino production processes and decay modes. Characteristic  $${{\tilde{G}}}$$  <math> <mover> <mi>G</mi> <mo>~</mo> </mover> </math>  -EWMSSM signal events have two or more Standard Model bosons and missing energy due to the escaping gravitinos. While much of the  $${{\tilde{G}}}$$  <math> <mover> <mi>G</mi> <mo>~</mo> </mover> </math>  -EWMSSM parameter space is excluded, we find several viable parameter regions that predict phenomenologically rich scenarios with multiple neutralinos and charginos within the kinematic reach of the LHC during Run 3, or the High Luminosity LHC. In particular, we identify scenarios with Higgsino-dominated electroweakinos as light as 140 GeV that are consistent with our combined set of collider searches and measurements. The full set of  $${{\tilde{G}}}$$  <math> <mover> <mi>G</mi> <mo>~</mo> </mover> </math>  -EWMSSM parameter samples and GAMBIT input files generated for this work is available via Zenodo.

Norway

Viktor Ananyev

Csaba Balázs

United Kingdom

Ankit Beniwal

Lasse Braseth

Andy Buckley

Jonathan Butterworth

Canada

Matthias Danninger

China

Andrew Fowlie

Anders Kvellestad

CERN

France

Farvah Mahmoudi

United States

Gregory Martinez

Markus Prim

Tomasz Procter

Are Raklev

Patrick Stöcker

Jeriek Abeele

Yang Zhang

Collider constraints on electroweakinos in the presence of a light gravitino

Simplified models provide a useful way to study the impacts of a small number of new particles on experimental observables and the interplay of those observables, without the need to construct an underlying theory. In this study, we perform global fits of simplified dark matter models with GAMBIT using an up-to-date set of likelihoods for indirect detection, direct detection and collider searches. We investigate models in which a scalar or fermionic dark matter candidate couples to quarks via an s-channel vector mediator. Large parts of parameter space survive for each model. In the case of Dirac or Majorana fermion dark matter, excesses in LHC monojet searches and relic density limits tend to prefer the resonance region, where the dark matter has approximately half the mass of the mediator. A combination of vector and axial-vector couplings to the Dirac candidate also leads to competing constraints from direct detection and unitarity violation.

We introduce the GAMBIT Universal Model Machine (GUM), a tool for automatically generating code for the global fitting software framework GAMBIT, based on Lagrangian-level inputs. GUM accepts models written symbolically in FeynRules and SARAH formats, and can use either tool along with MadGraph and CalcHEP to generate GAMBIT model, collider, dark matter, decay and spectrum code, as well as GAMBIT interfaces to corresponding versions of SPheno, micrOMEGAs, Pythia and Vevacious (C   ). In this paper we describe the features, methods, usage, pathways, assumptions and current limitations of GUM. We also give a fully worked example, consisting of the addition of a Majorana fermion simplified dark matter model with a scalar mediator to GAMBIT via GUM, and carry out a corresponding fit.

Sanjay Bloor

Sweden

José Camargo-Molina

Janina Renk

Peter Athron

The GAMBIT Universal Model Machine: from Lagrangians to likelihoods

The search for flavour-changing neutral current effects in B-meson decays is a powerful probe of physics beyond the Standard Model. Deviations from SM behaviour are often quantified by extracting the preferred values of the Wilson coefficients of an operator product expansion. We use the FlavBit module of the GAMBIT package to perform a simultaneous global fit of the Wilson coefficients  $$C_7$$  <math> <msub> <mi>C</mi> <mn>7</mn> </msub> </math>  ,  $$C_9$$  <math> <msub> <mi>C</mi> <mn>9</mn> </msub> </math>  , and  $$C_{10}$$  <math> <msub> <mi>C</mi> <mn>10</mn> </msub> </math>   using a combination of all current data on  $$b{\rightarrow }s\mu ^{+}\mu ^{-}$$  <math> <mrow> <mi>b</mi> <mo>→</mo> <mi>s</mi> <msup> <mi>μ</mi> <mo>+</mo> </msup> <msup> <mi>μ</mi> <mo>-</mo> </msup> </mrow> </math>   transitions. We further extend previous analyses by accounting for the correlated theoretical uncertainties at each point in the Wilson coefficient parameter space, rather than deriving the uncertainties from a Standard Model calculation. We find that the best fit deviates from the SM value with a significance of 6.6 $$\sigma $$  <math> <mi>σ</mi> </math>  . The largest deviation is associated with a vector coupling of muons to b and s quarks.

Poland

Jihyun Bhom

Marcin Chrzaszcz

A model-independent analysis of  $$b{\rightarrow }s\mu ^{+}\mu ^{-}$$  <math> <mrow> <mi>b</mi> <mo>→</mo> <mi>s</mi> <msup> <mi>μ</mi> <mo>+</mo> </msup> <msup> <mi>μ</mi> <mo>-</mo> </msup> </mrow> </math>  transitions with GAMBIT ’s FlavBit

We assess the status of a wide class of WIMP dark matter (DM) models in light of the latest experimental results using the global fitting framework GAMBIT. We perform a global analysis of effective field theory (EFT) operators describing the interactions between a gauge-singlet Dirac fermion and the Standard Model quarks, the gluons and the photon. In this bottom-up approach, we simultaneously vary the coefficients of 14 such operators up to dimension 7, along with the DM mass, the scale of new physics and several nuisance parameters. Our likelihood functions include the latest data from Planck, direct and indirect detection experiments, and the LHC. For DM masses below 100 GeV, we find that it is impossible to satisfy all constraints simultaneously while maintaining EFT validity at LHC energies. For new physics scales around 1 TeV, our results are influenced by several small excesses in the LHC data and depend on the prescription that we adopt to ensure EFT validity. Furthermore, we find large regions of viable parameter space where the EFT is valid and the relic density can be reproduced, implying that WIMPs can still account for the DM of the universe while being consistent with the latest data.

Neal Kozar

Belgium

Torsten Bringmann

Joachim Brod

Jonathan Cornell

Ben Farmer

Will Handley

Italy

Andre Scaffidi

Aaron Vincent

Sebastian Wild

Jure Zupan

Thermal WIMPs and the scale of new physics: global fits of Dirac dark matter effective field theories

The excess of electron recoil events seen by the XENON1T experiment has been interpreted as a potential signal of axion-like particles (ALPs), either produced in the Sun, or constituting part of the dark matter halo of the Milky Way. It has also been explained as a consequence of trace amounts of tritium in the experiment. We consider the evidence for the solar and dark-matter ALP hypotheses from the combination of XENON1T data and multiple astrophysical probes, including horizontal branch stars, red giants, and white dwarfs. We briefly address the influence of ALP decays and supernova cooling. While the different datasets are in clear tension for the case of solar ALPs, all measurements can be simultaneously accommodated for the case of a sub-dominant fraction of dark-matter ALPs. Nevertheless, this solution requires the tuning of several a priori unknown parameters, such that for our choices of priors a Bayesian analysis shows no strong preference for the ALP interpretation of the XENON1T excess over the background hypothesis.

J. Camargo-Molina

Sebastian Hoof

David Marsh

Wei Su

Lei Wu

Global fits of axion-like particles to XENON1T and astrophysical data

Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.

Melissa Beekveld

Netherlands

Sascha Caron

Barry Dillon

Spain

Eduardo Garrido-Merchán

Luc Hendriks

Iceland

Guðlaugur Jóhannesson

Adam Leinweber

Judita Mamužić

Sydney Otten

Roberto Austri

Zachary Searle

Bob Stienen

Joaquin Vanschoren

A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications

The evaluation of higher-order cross-sections is an important component in the search for new physics, both at hadron colliders and elsewhere. For most new physics processes of interest, total cross-sections are known at next-to-leading order (NLO) in the strong coupling  $$\alpha _s$$  <math> <msub> <mi>α</mi> <mi>s</mi> </msub> </math>  , and often beyond, via either higher-order terms at fixed powers of  $$\alpha _s$$  <math> <msub> <mi>α</mi> <mi>s</mi> </msub> </math>  , or multi-emission resummation. However, the computation time for such higher-order cross-sections is prohibitively expensive, and precludes efficient evaluation in parameter-space scans beyond two dimensions. Here we describe the software tool xsec, which allows for fast evaluation of cross-sections based on the use of machine-learning regression, using distributed Gaussian processes trained on a pre-generated sample of parameter points. This first version of the code provides all NLO Minimal Supersymmetric Standard Model strong-production cross-sections at the LHC, for individual flavour final states, evaluated in a fraction of a second. Moreover, it calculates regression errors, as well as estimates of errors from higher-order contributions, from uncertainties in the parton distribution functions, and from the value of  $$\alpha _s$$  <math> <msub> <mi>α</mi> <mi>s</mi> </msub> </math>  . While we focus on a specific phenomenological model of supersymmetry, the method readily generalises to any process where it is possible to generate a sufficient training sample.

Jon Sparre

Ingrid Vazquez-Holm

Xsec: the cross-section evaluation code