Maximizing Hadron Collider Sensitivity to Gauge-Mediated Supersymmetry Breaking Models

We consider typical hadron collider detector signals sensitive to delayed decays of the lightest neutralino to photon plus goldstino and demonstrate the potential for substantially increasing the portion of the general parameter space of a gauge-mediated supersymmetry breaking model that can be probed at the Tevatron.Comment: 11 pages, full postscript file is available via anonymous ftp at ftp://ucdhep.ucdavis.edu/gunion/gmsb.ps; incorrect labels on figures correcte

Fuzzy Chance-constrained Programming Based Security Information Optimization for Low Probability of Identification Enhancement in Radar Network Systems

In this paper, the problem of low probability of identification (LPID) improvement for radar network systems is investigated. Firstly, the security information is derived to evaluate the LPID performance for radar network. Then, without any prior knowledge of hostile intercept receiver, a novel fuzzy chance-constrained programming (FCCP) based security information optimization scheme is presented to achieve enhanced LPID performance in radar network systems, which focuses on minimizing the achievable mutual information (MI) at interceptor, while the attainable MI outage probability at radar network is enforced to be greater than a specified confidence level. Regarding to the complexity and uncertainty of electromagnetic environment in the modern battlefield, the trapezoidal fuzzy number is used to describe the threshold of achievable MI at radar network based on the credibility theory. Finally, the FCCP model is transformed to a crisp equivalent form with the property of trapezoidal fuzzy number. Numerical simulation results demonstrating the performance of the proposed strategy are provided

Ab Initio Simulation of the Nodal Surfaces of Heisenberg Antiferromagnets

The spin-half Heisenberg antiferromagnet (HAF) on the square and triangular lattices is studied using the coupled cluster method (CCM) technique of quantum many-body theory. The phase relations between different expansion coefficients of the ground-state wave function in an Ising basis for the square lattice HAF is exactly known via the Marshall-Peierls sign rule, although no equivalent sign rule has yet been obtained for the triangular lattice HAF. Here the CCM is used to give accurate estimates for the Ising-expansion coefficients for these systems, and CCM results are noted to be fully consistent with the Marshall-Peierls sign rule for the square lattice case. For the triangular lattice HAF, a heuristic rule is presented which fits our CCM results for the Ising-expansion coefficients of states which correspond to two-body excitations with respect to the reference state. It is also seen that Ising-expansion coefficients which describe localised, $m$-body excitations with respect to the reference state are found to be highly converged, and from this result we infer that the nodal surface of the triangular lattice HAF is being accurately modeled. Using these results, we are able to make suggestions regarding possible extensions of existing quantum Monte Carlo simulations for the triangular lattice HAF.Comment: 24 pages, Latex, 3 postscript figure

Complex Dynamics of Correlated Electrons in Molecular Double Ionization by an Ultrashort Intense Laser Pulse

With a semiclassical quasi-static model we achieve an insight into the complex dynamics of two correlated electrons under the combined influence of a two-center Coulomb potential and an intense laser field. The model calculation is able to reproduce experimental data of nitrogen molecules for a wide range of laser intensities from tunnelling to over-the-barrier regime, and predicts a significant alignment effect on the ratio of double over single ion yield. The classical trajectory analysis allows to unveil sub-cycle molecular double ionization dynamics.Comment: 5 pages, 5 figures. to appear in Phys. Rev. Lett.(2007

Classical Trajectory Perspective on Double Ionization Dynamics of Diatomic Molecules Irradiated by Ultrashort Intense Laser Pulses

In the present paper, we develop a semiclassical quasi-static model accounting for molecular double ionization in an intense laser pulse. With this model, we achieve insight into the dynamics of two highly-correlated valence electrons under the combined influence of a two-center Coulomb potential and an intense laser field, and reveal the significant influence of molecular alignment on the ratio of double over single ion yield. Analysis on the classical trajectories unveils sub-cycle dynamics of the molecular double ionization. Many interesting features, such as the accumulation of emitted electrons in the first and third quadrants of parallel momentum plane, the regular pattern of correlated momentum with respect to the time delay between closest collision and ionization moment, are revealed and successfully explained by back analyzing the classical trajectories. Quantitative agreement with experimental data over a wide range of laser intensities from tunneling to over-the-barrier regime is presented.Comment: 8 pages, 9 figure

Chiral geometry and rotational structure for 130^{130}Cs in the projected shell model

The projected shell model with configuration mixing for nuclear chirality is developed and applied to the observed rotational bands in the chiral nucleus $^{130}$Cs. For the chiral bands, the energy spectra and electromagnetic transition probabilities are well reproduced. The chiral geometry illustrated in the $K~plot$ and the $azithumal~plot$ is confirmed to be stable against the configuration mixing. The other rotational bands are also described in the same framework

A Comparative Study on the Use of Classification Algorithms in Financial Forecasting

Financial forecasting is a vital area in computational finance, where several studies have taken place over the years. One way of viewing financial forecasting is as a classification problem, where the goal is to find a model that represents the predictive relationships between predictor attribute values and class attribute values. In this paper we present a comparative study between two bio-inspired classification algorithms, a genetic programming algorithm especially designed for financial forecasting, and an ant colony optimization one, which is designed for classification problems. In addition, we compare the above algorithms with two other state-of-the-art classification algorithms, namely C4.5 and RIPPER. Results show that the ant colony optimization classification algorithm is very successful, significantly outperforming all other algorithms in the given classification problems, which provides insights for improving the design of specific financial forecasting algorithms