Statistical Challenges of Global SUSY Fits

We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorithmic difficulties of obtaining accurate profile likelihood estimates

Search for Higgs Bosons Decay H→γγH\to \gamma\gamma Using Vector Boson Fusion

The sensitivity of the ATLAS experiment to low mass SM Higgs produced via Vector Boson Fusion mechanism with $H\to \gamma\gamma$ is invest igated. A cut based event selection has been chosen to optimize the expected signal significance with this decay mode. A signal significance of 2. 2$\sigma$ may be achieved for M_H=130 \gev with 30 fb$^{-1}$ of accumulated luminosity

A Coverage Study of the CMSSM Based on ATLAS Sensitivity Using Fast Neural Networks Techniques

We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of ~ 10^4 with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.Comment: Further checks about accuracy of neural network approximation, fixed typos, added refs. Main results unchanged. Matches version accepted by JHE

Higgs Mass and Muon Anomalous Magnetic Moment in Supersymmetric Models with Vector-Like Matters

We study the muon anomalous magnetic moment (muon g-2) and the Higgs boson mass in a simple extension of the minimal supersymmetric (SUSY) Standard Model with extra vector-like matters, in the frameworks of gauge mediated SUSY breaking (GMSB) models and gravity mediation (mSUGRA) models. It is shown that the deviation of the muon g-2 and a relatively heavy Higgs boson can be simultaneously explained in large tan-beta region. (i) In GMSB models, the Higgs mass can be more than 135 GeV (130 GeV) in the region where muon g-2 is consistent with the experimental value at the 2 sigma (1 sigma) level, while maintaining the perturbative coupling unification. (ii) In the case of mSUGRA models with universal soft masses, the Higgs mass can be as large as about 130 GeV when muon g-2 is consistent with the experimental value at the 2 sigma level. In both cases, the Higgs mass can be above 140 GeV if the g-2 constraint is not imposed.Comment: 26 pages; 7 figures; corrected typos; minor change

Natural priors, CMSSM fits and LHC weather forecasts

Previous LHC forecasts for the constrained minimal supersymmetric standard model (CMSSM), based on current astrophysical and laboratory measurements, have used priors that are flat in the parameter tan beta, while being constrained to postdict the central experimental value of MZ. We construct a different, new and more natural prior with a measure in mu and B (the more fundamental MSSM parameters from which tan beta and MZ are actually derived). We find that as a consequence this choice leads to a well defined fine-tuning measure in the parameter space. We investigate the effect of such on global CMSSM fits to indirect constraints, providing posterior probability distributions for Large Hadron Collider (LHC) sparticle production cross sections. The change in priors has a significant effect, strongly suppressing the pseudoscalar Higgs boson dark matter annihilation region, and diminishing the probable values of sparticle masses. We also show how to interpret fit information from a Markov Chain Monte Carlo in a frequentist fashion; namely by using the profile likelihood. Bayesian and frequentist interpretations of CMSSM fits are compared and contrasted

X-Ray Determination of the Variable Rate of Mass Accretion onto TW Hydrae

Diagnostics of electron temperature (T_e), electron density (n_e), and hydrogen column density (N_H) from the Chandra High Energy Transmission Grating spectrum of He-like Ne IX in TW Hydrae (TW Hya), in conjunction with a classical accretion model, allow us to infer the accretion rate onto the star directly from measurements of the accreting material. The new method introduces the use of the absorption of Ne IX lines as a measure of the column density of the intervening, accreting material. On average, the derived mass accretion rate for TW Hya is 1.5 x 10^{-9} M_{\odot} yr^{-1}, for a stellar magnetic field strength of 600 Gauss and a filling factor of 3.5%. Three individual Chandra exposures show statistically significant differences in the Ne IX line ratios, indicating changes in N_H, T_e, and n_e by factors of 0.28, 1.6, and 1.3, respectively. In exposures separated by 2.7 days, the observations reported here suggest a five-fold reduction in the accretion rate. This powerful new technique promises to substantially improve our understanding of the accretion process in young stars