A global fit of the MSSM with GAMBIT

Athron, Peter; Balázs, Csaba; Bringmann, Torsten; Buckley, A. G.; Chrząszcz, M.; Conrad, J.; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Benjamin; Jackson, P.; Krislock, Abram; Kvellestad, Anders; Mahmoudi, F.; Martinez, Gregory D.; Putze, A.; Raklev, Are; Rogan, C.; Saavedra, A. F.; Savage, Christopher; Scott, Pat; Serra, N.; Weniger, Christoph; White, M. J.

doi:10.1140/epjc/s10052-017-5196-8

Cited by 120 publications

(161 citation statements)

References 321 publications

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“…Basic examples of how to use FlavBit in a GAMBIT BSM global fit can be found in any of the canonical GAMBIT SUSY examples in the yaml_files directory: CMSSM.yaml, NUHM1.yaml, NUHM2.yaml or MSSM7.yaml [4,10,11]. In this section, we go through a number of flavour-specific examples, ranging from flavour-only supersymmetric and effective field theory scans with GAMBIT, to an example of how to use FlavBit in standalone mode.…”

Section: Examplesmentioning

confidence: 99%

“…FlavBit takes into account all theoretical and experimental correlations between the different observables. The resulting likelihoods can be incorporated into the GAMBIT global likelihood to scan the parameter spaces of various models for new physics [4,[8][9][10][11], taking into account complementary constraints from direct production [12], dark matter searches [13], and SM and related precision measurements [14].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

FlavBit: a GAMBIT module for computing flavour observables and likelihoods

Bernlochner¹,

Chrząszcz²,

Dal³

et al. 2017

Eur. Phys. J. C

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Flavour physics observables are excellent probes of new physics up to very high energy scales. Here we present FlavBit, the dedicated flavour physics module of the globalfitting package GAMBIT. FlavBit includes custom implementations of various likelihood routines for a wide range of flavour observables, including detailed uncertainties and correlations associated with LHCb measurements of rare, leptonic and semileptonic decays of B and D mesons, kaons and pions. It provides a generalised interface to external theory codes such as SuperIso, allowing users to calculate flavour observables in and beyond the Standard Model, and then test them in detail against all relevant experimental data. We describe FlavBit and its constituent physics in some detail, then give examples from supersymmetry and effective field theory illustrating how it can be used both as a standalone library for flavour physics, and within GAMBIT.

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Section: Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FlavBit: a GAMBIT module for computing flavour observables and likelihoods

Bernlochner¹,

Chrząszcz²,

Dal³

et al. 2017

Eur. Phys. J. C

Self Cite

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show abstract

“…Note that choosing a more complicated model, with more complicated parameters in the 'higher' dimensions, would only increase the required computing time, making such an extensive comparison study infeasible. We refer the interested reader to the companion papers on supersymmetric models [33,34] for applications of Diver and MultiNest to higher-dimensional multimodal parameter spaces.…”

Section: Scanner Performance Comparisonsmentioning

confidence: 99%

Comparison of statistical sampling methods with ScannerBit, the GAMBIT scanning module

Martinez¹,

McKay²,

Farmer³

et al. 2017

Eur. Phys. J. C

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100

160

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We introduce ScannerBit, the statistics and sampling module of the public, open-source global fitting framework GAMBIT. ScannerBit provides a standardised interface to different sampling algorithms, enabling the use and comparison of multiple computational methods for inferring profile likelihoods, Bayesian posteriors, and other statistical quantities. The current version offers random, grid, raster, nested sampling, differential evolution, Markov Chain Monte Carlo (MCMC) and ensemble Monte Carlo samplers. We also announce the release of a new standalone differential evolution sampler, Diver, and describe its design, usage and interface to ScannerBit. We subject Diver and three other samplers (the nested sampler MultiNest, the MCMC GreAT, and the native ScannerBit implementation of the ensemble Monte Carlo algorithm T-Walk) to a battery of statistical tests. For this we use a realistic physical likelihood function, based on the scalar singlet model of dark matter. We examine the performance of each sampler as a function of its adjustable settings, and the dimensionality of the sampling problem. We evaluate performance on four metrics: optimality of the best fit found, completeness in exploring the best-fit region, number of likelihood evaluations, and total runtime. For Bayesian posterior estimation at high resolution, T-Walk provides the most accurate and timely mapping of the full parameter space. For profile likelihood analysis in less than about ten dimensions, we find that Diver and MultiNest score similarly in terms of best fit and speed, outperforming GreAT a

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“…There have been several studies combining the LHC limits and dark matter constraints in the pMSSM, which either aim at determining the excluded regions or perform global fits in order to find the preferred parameter regions (see e.g. [7][8][9][10][11][12][13][14] for some recent studies). Instead, the focus here will be on the astrophysical and cosmological uncertainties that can affect the interpretation of the dark matter experiment results, and to show explicitly and quantify the impact of such uncertainties in the dark matter limits that are set on the MSSM parameters.…”

Section: Jhep11(2017)132mentioning

confidence: 99%

Robustness of dark matter constraints and interplay with collider searches for New Physics

Arbey

Robbins

Mahmoudi

et al. 2017

J. High Energ. Phys.

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Abstract:We study the implications of dark matter searches, together with collider constraints, on the phenomenological MSSM with neutralino dark matter and focus on the consequences of the related uncertainties in some detail. We consider, inter alia, the latest results from AMS-02, Fermi-LAT and XENON1T. In particular, we examine the impact of the choice of the dark matter halo profile, as well as the propagation model for cosmic rays, for dark matter indirect detection and show that the constraints on the MSSM differ by one to two orders of magnitude depending on the astrophysical hypotheses. On the other hand, our limited knowledge of the local relic density in the vicinity of the Earth and the velocity of Earth in the dark matter halo leads to a factor 3 in the exclusion limits obtained by direct detection experiments. We identified the astrophysical models leading to the most conservative and the most stringent constraints and for each case studied the complementarities with the latest LHC measurements and limits from Higgs, SUSY and monojet searches. We show that combining all data from dark matter searches and colliders, a large fraction of our supersymmetric sample could be probed. Whereas the direct detection constraints are rather robust under the astrophysical assumptions, the uncertainties related to indirect detection can have an important impact on the number of the excluded points.

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A global fit of the MSSM with GAMBIT

Cited by 120 publications

References 321 publications

FlavBit: a GAMBIT module for computing flavour observables and likelihoods

FlavBit: a GAMBIT module for computing flavour observables and likelihoods

Comparison of statistical sampling methods with ScannerBit, the GAMBIT scanning module

Robustness of dark matter constraints and interplay with collider searches for New Physics

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