Roszkowski, L., Ruiz de Austri, R., Trotta, R., Tsai, Y. L. S., & Varley, T. A. (2011). Global fits of the nonuniversal Higgs model. Phys. Rev. D, 83(1), 015014–19pp.
Abstract: We carry out global fits to the nonuniversal Higgs Model (NUHM), applying all relevant present-day constraints. We present global probability maps for the NUHM parameters and observables (including collider signatures, direct, and indirect detection quantities), both in terms of posterior probabilities and in terms of profile likelihood maps. We identify regions of the parameter space where the neutralino dark matter in the model is either binolike, or else higgsinolike with mass close to 1 TeV and a spin-independent scattering cross section similar to 10(-9)-10(-8) pb. We trace the occurrence of the higgsinolike region to be a consequence of a mild focusing effect in the running of one of the Higgs masses, the existence of which in the NUHM we identify in our analysis. Although the usual binolike neutralino is more prominent, higgsinolike dark matter cannot be excluded, however its significance strongly depends on the prior and statistics used to assess it. We note that, despite experimental constraints often favoring different regions of parameter space to the constrained minimal supersymmetric standard model, most observational consequences appear fairly similar, which will make it challenging to distinguish the two models experimentally.
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Allanach, B. C., Martin, S. P., Robertson, D. G., & Ruiz de Austri, R. (2017). The inclusion of two-loop SUSYQCD corrections to gluino and squark pole masses in the minimal and next-to-minimal supersymmetric standard model: SOFTSUSY3.7. Comput. Phys. Commun., 219, 339–345.
Abstract: We describe an extension of the SOFTSUSY spectrum calculator to include two-loop supersymmetric QCD (SUSYQCD) corrections of order O(alpha(2)(s)) to gluino and squark pole masses, either in the minimal supersymmetric standard model (MSSM) or the next-to-minimal supersymmetric standard model (NMSSM). This document provides an overview of the program and acts as a manual for the new version of SOFTSUSY, which includes the increase in accuracy in squark and gluino pole mass predictions. Program summary Program title: SOFTSUSY Program Files doi: http://dx.doLorg/10.17632/sh77x9j7hs.1 Licensing provisions: GNU GPLv3 Programming language: C++, fortran, C Nature of problem: Calculating supersymmetric particle spectrum, mixing parameters and couplings in the MSSM or the NMSSM. The solution to the renormalization group equations must be consistent with theoretical boundary conditions on supersymmetry breaking parameters, as well as a weak-scale boundary condition on gauge couplings, Yukawa couplings and the Higgs potential parameters. Solution method: Nested fixed point iteration. Restrictions: SOFTSUSY will provide a solution only in the perturbative regime and it assumes that all couplings of the model are real (i.e. CP-conserving). If the parameter point under investigation is nonphysical for some reason (for example because the electroWeak potential does not have an acceptable minimum), SOFTSUSY returns an error message. The higher order corrections included are for the MSSM (R-parity conserving or violating) or the real R-parity conserving NMSSM only. Journal reference of previous version: Comput. Phys. Comm. 189 (2015) 192. Does the new version supersede the previous version?: Yes. Reasons for the new version: It is desirable to improve the accuracy of the squark and gluinos mass predictions, since they strongly affect supersymmetric particle production cross-sections at colliders. Summary of revisions: The calculation of the squark and gluino pole masses is extended to be of next-to next-to leading order in SUSYQCD, i.e. including terms up to O(g(s)(4)/(16 pi(2))(2)). Additional comments: Program obtainable from http://softsusy.hepforge.org/
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Aarrestad, T. et al, Mamuzic, J., & Ruiz de Austri, R. (2022). Benchmark data and model independent event classification for the large hadron collider. SciPost Phys., 12(1), 043–57pp.
Abstract: We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of > 1 billion simulated LHC events corresponding to 10 fb(-1) of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge.
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Gunion, J. F., Lopez-Fogliani, D. E., Roszkowski, L., Ruiz de Austri, R., & Varley, T. A. (2011). Next-to-minimal supersymmetric model Higgs scenarios for partially universal GUT scale boundary conditions. Phys. Rev. D, 84(5), 055026–17pp.
Abstract: We examine the extent to which it is possible to realize the NMSSM “ideal Higgs” models espoused in several papers by Gunion et al. in the context of partially universal GUT scale boundary conditions. To this end we use the powerful methodology of nested sampling. We pay particular attention to whether ideal-Higgs-like points not only pass LEP constraints but are also acceptable in terms of the numerous constraints now available, including those from the Tevatron and B-factory data, (g – 2)(mu) and the relic density Omega h(2). In general for this particular methodology and range of parameters chosen, very few points corresponding to said previous studies were found, and those that were found were at best 2 sigma away from the preferred relic density value. Instead, there exist a class of points, which combine a mostly singlet-like Higgs with a mostly singlino-like neutralino coannihilating with the lightest stau, that are able to effectively pass all implemented constraints in the region 80 < m(h) < 100. It seems that the spin-independent direct detection cross section acts as a key discriminator between ideal Higgs points and the hard to detect singlino-like points.
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Ellis, J., Gomez, M. E., Lola, S., Ruiz de Austri, R., & Shafi, Q. (2020). Confronting grand unification with lepton flavour violation, dark matter and LHC data. J. High Energy Phys., 09(9), 197–29pp.
Abstract: We explore possible signatures for charged lepton flavour violation (LFV), sparticle discovery at the LHC and dark matter (DM) searches in grand unified theories (GUTs) based on SU(5), flipped SU(5) (FSU(5)) and SU(4)(c) x SU(2)(L) x SU(2)(R) (4-2-2). We assume that soft supersymmetry-breaking terms preserve the group symmetry at some high input scale, and focus on the non-universal effects on different matter representations generated by gauge interactions at lower scales, as well as the charged LFV induced in Type-1 see-saw models of neutrino masses. We identify the different mechanisms that control the relic DM density in the various GUT models, and contrast their LFV and LHC signatures. The SU(5) and 4-2-2 models offer good detection prospects both at the LHC and in LFV searches, though with different LSP compositions, and the SU(5) and FSU(5) models offer LFV within the current reach. The 4-2-2 model allows chargino and gluino coannihilations with neutralinos, and the former offer good detection prospects for both the LHC and LFV, while gluino coannihilations lead to lower LFV rates. Our results indicate that LFV is a powerful tool that complements LHC and DM searches, providing significant insights into the sparticle spectra and neutrino mass parameters in different models.
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