Lone Higgs at the LHC

We address the possible scenario that the Large Hadron Collider (LHC) discovers only a Higgs boson after 10 fb^{-1} of operation, and attempt to identify this Higgs boson as that of the Standard Model (SM), the minimal universal extra dimension model (MUED), the littlest Higgs model with T-parity (LHT), or the minimal supersymmetric Standard Model (MSSM), using only the measurement of the product of gluon-fusion production cross section and the di-photon branching ratio. In MUED, by decoupling any new physics sufficiently to evade the discovery reach at the LHC, the deviation of the signal from the SM is not statistically significant. However, in LHT and MSSM, it is possible to have a significant deviation in the signal that is consistent with this "lone Higgs scenario", and, in the case of a very large suppression, we can distinguish MSSM and LHT before the discovery of any new resonances. Starting with the lone Higgs scenario and the deviation in this measurement from the Standard Model prediction (whether or not statistically significant), we offer tests that may discriminate the models and search strategies of discovering new physics signatures with increasing integrated luminosity.Comment: 32 pages, 25 figures, PRD versio

A Lower Bound of 2n2^n Conditional Branches for Boolean Satisfiability on Post Machines

We establish a lower bound of $2^n$ conditional branches for deciding the satisfiability of the conjunction of any two Boolean formulas from a set called a full representation of Boolean functions of $n$ variables - a set containing a Boolean formula to represent each Boolean function of $n$ variables. The contradiction proof first assumes that there exists a Post machine (Post's Formulation 1) that correctly decides the satisfiability of the conjunction of any two Boolean formulas from such a set by following an execution path that includes fewer than $2^n$ conditional branches. By using multiple runs of this Post machine, with one run for each Boolean function of $n$ variables, the proof derives a contradiction by showing that this Post machine is unable to correctly decide the satisfiability of the conjunction of at least one pair of Boolean formulas from a full representation of $n$-variable Boolean functions if the machine executes fewer than $2^n$ conditional branches. This lower bound of $2^n$ conditional branches holds for any full representation of Boolean functions of $n$ variables, even if a full representation consists solely of minimized Boolean formulas derived by a Boolean minimization method. We discuss why the lower bound fails to hold for satisfiability of certain restricted formulas, such as 2CNF satisfiability, XOR-SAT, and HORN-SAT. We also relate the lower bound to 3CNF satisfiability. The lower bound does not depend on sequentiality of access to the boxes in the symbol space and will hold even if a machine is capable of non-sequential access.Comment: This article draws heavily from arXiv:1406.597

Medial Ganglionic Eminence Progenitors Transplanted into Hippocampus Integrate in a Functional and Subtype-Appropriate Manner.

Medial ganglionic eminence (MGE) transplantation rescues disease phenotypes in various preclinical models with interneuron deficiency or dysfunction, including epilepsy. While underlying mechanism(s) remains unclear to date, a simple explanation is that appropriate synaptic integration of MGE-derived interneurons elevates GABA-mediated inhibition and modifies the firing activity of excitatory neurons in the host brain. However, given the complexity of interneurons and potential for transplant-derived interneurons to integrate or alter the host network in unexpected ways, it remains unexplored whether synaptic connections formed by transplant-derived interneurons safely mirror those associated with endogenous interneurons. Here, we combined optogenetics, interneuron-specific Cre driver mouse lines, and electrophysiology to study synaptic integration of MGE progenitors. We demonstrated that MGE-derived interneurons, when transplanted into the hippocampus of neonatal mice, migrate in the host brain, differentiate to mature inhibitory interneurons, and form appropriate synaptic connections with native pyramidal neurons. Endogenous and transplant-derived MGE progenitors preferentially formed inhibitory synaptic connections onto pyramidal neurons but not endogenous interneurons. These findings demonstrate that transplanted MGE progenitors functionally integrate into the postnatal hippocampal network

Evaluation of aerothermal modeling computer programs

Various computer programs based upon the SIMPLE or SIMPLER algorithm were studied and compared for numerical accuracy, efficiency, and grid dependency. Four two-dimensional and one three-dimensional code originally developed by a number of research groups were considered. In general, the accuracy and computational efficieny of these TEACH type programs were improved by modifying the differencing schemes and their solvers. A brief description of each program is given. Error reduction, spline flux and second upwind differencing programs are covered

Insights into antibody catalysis: Structure of an oxygenation catalyst at 1.9-Å resolution

The x-ray crystal structures of the sulfide oxidase antibody 28B4 and of antibody 28B4 complexed with hapten have been solved at 2.2-Å and 1.9-Å resolution, respectively. To our knowledge, these structures are the highest resolution catalytic antibody structures to date and provide insight into the molecular mechanism of this antibody-catalyzed monooxygenation reaction. Specifically, the data suggest that entropic restriction plays a fundamental role in catalysis through the precise alignment of the thioether substrate and oxidant. The antibody active site also stabilizes developing charge on both sulfur and periodate in the transition state via cation-pi and electrostatic interactions, respectively. In addition to demonstrating that the active site of antibody 28B4 does indeed reflect the mechanistic information programmed in the aminophosphonic acid hapten, these high-resolution structures provide a basis for enhancing turnover rates through mutagenesis and improved hapten design

Estimating Luminosities and Stellar Masses of Galaxies Photometrically without Determining Redshifts

Large direct-imaging surveys usually use a template-fitting technique to estimate photometric redshifts for galaxies, which are then applied to derive important galaxy properties such as luminosities and stellar masses. These estimates can be noisy and suffer from systematic biases because of the possible mis-selection of templates and the propagation of the photometric redshift uncertainty. We introduce an algorithm, the Direct Empirical Photometric method (DEmP), which can be used to directly estimate these quantities using training sets, bypassing photometric redshift determination. DEmP also applies two techniques to minimize the effects arising from the non-uniform distribution of training-set galaxy redshifts from a flux-limited sample. First, for each input galaxy, fitting is performed using a subset of the training-set galaxies with photometry and colors closest to those of the input galaxy. Second, the training set is artificially resampled to produce a flat distribution in redshift, or other properties, e.g., luminosity. To test the performance of DEmP, we use a 4-filter-band mock catalog to examine its ability to recover redshift, luminosity, stellar mass, and luminosity and stellar-mass functions. We also compare the results to those from two publicly available template-fitting methods, finding that the DEmP algorithm outperforms both. We find resampling the training set to have a uniform redshift distribution produces the best results not only in photometric redshift, but also in estimating luminosity and stellar mass. The DEmP method is especially powerful in estimating quantities such as near-IR luminosities and stellar mass using only data from a small number of optical bands.Comment: 17 Pages, 7 figures, accepted for publication in Ap

Nonadiabatic Dynamics in Open Quantum-Classical Systems: Forward-Backward Trajectory Solution

A new approximate solution to the quantum-classical Liouville equation is derived starting from the formal solution of this equation in forward-backward form. The time evolution of a mixed quantum-classical system described by this equation is obtained in a coherent state basis using the mapping representation, which expresses $N$ quantum degrees of freedom in a 2N-dimensional phase space. The solution yields a simple non-Hamiltonian dynamics in which a set of $N$ coherent state coordinates evolve in forward and backward trajectories while the bath coordinates evolve under the influence of the mean potential that depends on these forward and backward trajectories. It is shown that the solution satisfies the differential form of the quantum-classical Liouville equation exactly. Relations to other mixed quantum-classical and semi-classical schemes are discussed.Comment: 28 pages, 1 figur