Constraints on Higgs Properties and SUSY Partners in the pMSSM

Direct searches for superpartners and precision measurements of the properties of the $\sim 126$ GeV Higgs boson lead to important inter-dependent constraints on the underlying parameter space of the MSSM. The 19/20-parameter p(henomenological)MSSM offers a flexible framework for the study of a wide variety of both Higgs and SUSY phenomena at the LHC and elsewhere. Within this scenario we address the following questions: `What will potentially null searches for SUSY at the LHC tell us about the possible properties of the Higgs boson?' and, conversely, `What do precision measurements of the properties of the Higgs tell us about the possible properties of the various superpartners?' Clearly the answers to such questions will be functions of both the collision energy of the LHC as well as the accumulated integrated luminosity. We address these questions employing several sets of pMSSM models having either neutralino or gravitino LSPs, making use of the ATLAS SUSY analyses at the 7/8 TeV LHC as well as planned SUSY and Higgs analyses at the 14 TeV LHC and the ILC. Except for theoretical uncertainties that remain to be accounted for in the ratios of SUSY and SM couplings, we demonstrate that Higgs coupling measurements at the 14 TeV LHC, and particularly at the 500 GeV ILC, will be sensitive to regions of the pMSSM model space that are not accessible to direct SUSY searches.Comment: 23 pages, 9 figures. Contributed to the Community Summer Study 2013, Minneapolis, MN July 29 - August 6, 201

A Data-Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition

The Koopman operator is a linear but infinite dimensional operator that governs the evolution of scalar observables defined on the state space of an autonomous dynamical system, and is a powerful tool for the analysis and decomposition of nonlinear dynamical systems. In this manuscript, we present a data driven method for approximating the leading eigenvalues, eigenfunctions, and modes of the Koopman operator. The method requires a data set of snapshot pairs and a dictionary of scalar observables, but does not require explicit governing equations or interaction with a "black box" integrator. We will show that this approach is, in effect, an extension of Dynamic Mode Decomposition (DMD), which has been used to approximate the Koopman eigenvalues and modes. Furthermore, if the data provided to the method are generated by a Markov process instead of a deterministic dynamical system, the algorithm approximates the eigenfunctions of the Kolmogorov backward equation, which could be considered as the "stochastic Koopman operator" [1]. Finally, four illustrative examples are presented: two that highlight the quantitative performance of the method when presented with either deterministic or stochastic data, and two that show potential applications of the Koopman eigenfunctions

Identifying Finite-Time Coherent Sets from Limited Quantities of Lagrangian Data

A data-driven procedure for identifying the dominant transport barriers in a time-varying flow from limited quantities of Lagrangian data is presented. Our approach partitions state space into pairs of coherent sets, which are sets of initial conditions chosen to minimize the number of trajectories that "leak" from one set to the other under the influence of a stochastic flow field during a pre-specified interval in time. In practice, this partition is computed by posing an optimization problem, which once solved, yields a pair of functions whose signs determine set membership. From prior experience with synthetic, "data rich" test problems and conceptually related methods based on approximations of the Perron-Frobenius operator, we observe that the functions of interest typically appear to be smooth. As a result, given a fixed amount of data our approach, which can use sets of globally supported basis functions, has the potential to more accurately approximate the desired functions than other functions tailored to use compactly supported indicator functions. This difference enables our approach to produce effective approximations of pairs of coherent sets in problems with relatively limited quantities of Lagrangian data, which is usually the case with real geophysical data. We apply this method to three examples of increasing complexity: the first is the double gyre, the second is the Bickley Jet, and the third is data from numerically simulated drifters in the Sulu Sea.Comment: 14 pages, 7 figure

Does Administration Timing of Ondansetron, a 5-HT3 Receptor Antagonist, Affect Inhibition of the Bezold-Jarisch Reflex in OB C-section Patients Receiving Spinal Anesthesia

Ondansetron (a 5HT-3 receptor antagonist) has been shown in multiple randomized controlled trials (RCT’s) and meta-analysis to inhibit activation of Bezold-Jarisch Reflex (BJR) in response to spinal anesthesia for elective cesarean section patients. Studies have not determined whether the timing of administration changes the inhibitory affect of ondansetron in this patient population. This project addressed the following question: Does administration timing of Ondansetron, a 5-HT3 receptor antagonist, affect inhibition of the Bezold-Jarisch Reflex in obstetric cesarean section patients receiving spinal anesthesia? De-identified aggregated electronic medical record data for a one-year period was obtained. Data was grouped by ondansetron administration timing prior to spinal administration: ≤ 15 minutes (G1), \u3e 15 minutes and ≤ 30 minutes (G2), \u3e 30 minutes (G3). Blood Pressure (BP) data, including systolic, diastolic and mean arterial pressure (MAP), was included for four time points: pre spinal, 5-, 15- and 30-minutes post spinal. Change in BP from baseline were used for analysis. Total vasopressor usage was also included for analysis. Sixty-six obstetric cases were included, (G1 n=24), (G2 n=24) and (G3 n=18). Data was analyzed using the one-way ANOVA test for BP change scores and the Kruskal-Wallis for evaluating vasopressor use. No statistical significance between groups was found in BP change scores or vasopressor use. However, G3 did show greater drops in BP and increased vasopressor usage compared to G2 and G1. Further evaluation is recommended through either a large-scale retrospective study or randomized control trial (RCT)

More Energy, More Searches, but the pMSSM Lives On

We further examine the capability of the 7 and 8 TeV LHC to explore the parameter space of the p(henomenological)MSSM with neutralino LSPs. Here we present an updated study employing all of the relevant ATLAS SUSY analyses, as well as all relevant LHC non-MET searches, whose data were publically available as of mid-September 2012. We find that roughly 1/3 of our pMSSM model points are excluded at present with an important role being played by both the heavy flavor and multi-lepton searches, as well as those for heavy stable charged particles. Nonetheless, we find that light gluinos, 1st/2nd generation squarks, and stop/sbottoms (\lsim 400-700 GeV), as well as models with 1% fine-tuning or better, are still viable in the pMSSM. In addition, we see that increased luminosity at 8 TeV is unlikely to significantly improve the reach of the "vanilla" searches. The impact of these null searches on the SUSY sparticle spectrum is discussed in detail and the implications of these results for models with low fine-tuning, a future lepton collider and dark matter searches are examined.Comment: 33 pages, 9 figure