New techniques for chargino-neutralino detection at LHC

The recent LHC discovery of a Higgs-like boson at 126 GeV has important consequences for SUSY, pushing the spectrum of strong-interacting supersymmetric particles to high energies, very difficult to probe at the LHC. This gives extra motivation to study the direct production of electroweak particles, as charginos and neutralinos, which are presently very poorly constrained. The aim of this work is to improve the analysis of chargino-neutralino pair production at LHC, focusing on the kinematics of the processes. We propose a new method based on the study of the poles of a certain kinematical variable. This complements other approaches, giving new information about the spectrum and improving the signal-to-background ratio. We illustrate the method in particular SUSY models, and show that working with the LHC at 100/fb luminosity one would be able to distinguish the SUSY signal from the Standard Model background.Comment: accepted for publication in JHE

Reducing the fine-tuning of gauge-mediated SUSY breaking

Despite their appealing features, models with gauge-mediated supersymmetry breaking (GMSB) typically present a high degree of fine-tuning, due to the initial absence of the top trilinear scalar couplings, $A_t=0$. In this paper, we carefully evaluate such a tuning, showing that is worse than per mil in the minimal model. Then, we examine some existing proposals to generate $A_t\neq 0$ term in this context. We find that, although the stops can be made lighter, usually the tuning does not improve (it may be even worse), with some exceptions, which involve the generation of $A_t$ at one loop or tree level. We examine both possibilities and propose a conceptually simplified version of the latter; which is arguably the optimum GMSB setup (with minimal matter content), concerning the fine-tuning issue. The resulting fine-tuning is better than one per mil, still severe but similar to other minimal supersymmetric standard model constructions. We also explore the so-called "little $A_t^2/m^2$ problem", i.e. the fact that a large $A_t$-term is normally accompanied by a similar or larger sfermion mass, which typically implies an increase in the fine-tuning. Finally, we find the version of GMSB for which this ratio is optimized, which, nevertheless, does not minimize the fine-tuning.Comment: 16 pages, 11 figures, 1 appendix. Discussion extended, matches EPJC published versio

The health of SUSY after the Higgs discovery and the XENON100 data

We analyze the implications for the status and prospects of supersymmetry of the Higgs discovery and the last XENON data. We focus mainly, but not only, on the CMSSM and NUHM models. Using a Bayesian approach we determine the distribution of probability in the parameter space of these scenarios. This shows that, most probably, they are now beyond the LHC reach . This negative chances increase further (at more than 95% c.l.) if one includes dark matter constraints in the analysis, in particular the last XENON100 data. However, the models would be probed completely by XENON1T. The mass of the LSP neutralino gets essentially fixed around 1 TeV. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises automatically from the careful Bayesian analysis itself, and allows to scan the whole parameter space. In this way, we can explain and resolve the apparent discrepancies between the previous results in the literature. Although SUSY has become hard to detect at LHC, this does not necessarily mean that is very fine-tuned. We use Bayesian techniques to show the experimental Higgs mass is at $\sim 2\ \sigma$ off the CMSSM or NUHM expectation. This is substantial but not dramatic. Although the CMSSM or the NUHM are unlikely to show up at the LHC, they are still interesting and plausible models after the Higgs observation; and, if they are true, the chances of discovering them in future dark matter experiments are quite high

What is a Natural SUSY scenario?

The idea of "Natural SUSY", understood as a supersymmetric scenario where the fine-tuning is as mild as possible, is a reasonable guide to explore supersymmetric phenomenology. In this paper, we re-examine this issue in the context of the MSSM including several improvements, such as the mixing of the fine-tuning conditions for different soft terms and the presence of potential extra fine-tunings that must be combined with the electroweak one. We give tables and plots that allow to easily evaluate the fine-tuning and the corresponding naturalness bounds for any theoretical model defined at any high-energy (HE) scale. Then, we analyze in detail the complete fine-tuning bounds for the unconstrained MSSM, defined at any HE scale. We show that Natural SUSY does not demand light stops. Actually, an average stop mass below 800 GeV is disfavored, though one of the stops might be very light. Regarding phenomenology, the most stringent upper bound from naturalness is the one on the gluino mass, which typically sets the present level of fine-tuning at ${\cal O}(1\%)$. However, this result presents a strong dependence on the HE scale. E.g. if the latter is $10^7$ GeV the level of fine-tuning is $\sim$ four times less severe. Finally, the most robust result of Natural SUSY is by far that Higgsinos should be rather light, certainly below 700 GeV for a fine-tuning of ${\cal O}(1\%)$ or milder. Incidentally, this upper bound is not far from $\simeq1$ TeV, which is the value required if dark matter is made of Higgsinos.Comment: 41 pages, 8 figures, 9 tables. References added, matches JHEP published versio

Quantifying the tension between the Higgs mass and (g-2)_mu in the CMSSM

Supersymmetry has been often invoqued as the new physics that might reconcile the experimental muon magnetic anomaly, a_mu, with the theoretical prediction (basing the computation of the hadronic contribution on e^+ e^- data). However, in the context of the CMSSM, the required supersymmetric contributions (which grow with decreasing supersymmetric masses) are in potential tension with a possibly large Higgs mass (which requires large stop masses). In the limit of very large m_h supersymmetry gets decoupled, and the CMSSM must show the same discrepancy as the SM with a_mu . But it is much less clear for which size of m_h does the tension start to be unbearable. In this paper, we quantify this tension with the help of Bayesian techniques. We find that for m_h > 125 GeV the maximum level of discrepancy given current data (~ 3.3 sigma) is already achieved. Requiring less than 3 sigma discrepancy, implies m_h < 120 GeV. For a larger Higgs mass we should give up either the CMSSM model or the computation of a_mu based on e^+ e^-; or accept living with such inconsistency

Bayesian approach and Naturalness in MSSM analyses for the LHC

The start of LHC has motivated an effort to determine the relative probability of the different regions of the MSSM parameter space, taking into account the present, theoretical and experimental, wisdom about the model. Since the present experimental data are not powerful enough to select a small region of the MSSM parameter space, the choice of a judicious prior probability for the parameters becomes most relevant. Previous studies have proposed theoretical priors that incorporate some (conventional) measure of the fine-tuning, to penalize unnatural possibilities. However, we show that such penalization arises from the Bayesian analysis itself (with no ad hoc assumptions), upon the marginalization of the mu-parameter. Furthermore the resulting effective prior contains precisely the Barbieri-Giudice measure, which is very satisfactory. On the other hand we carry on a rigorous treatment of the Yukawa couplings, showing in particular that the usual practice of taking the Yukawas "as required", approximately corresponds to taking logarithmically flat priors in the Yukawa couplings. Finally, we use an efficient set of variables to scan the MSSM parameter space, trading in particular B by tan beta, giving the effective prior in the new parameters. Beside the numerical results, we give accurate analytic expressions for the effective priors in all cases. Whatever experimental information one may use in the future, it is to be weighted by the Bayesian factors worked out here.Comment: LaTeX, 19 pages, 3 figure